All India Institute of Speech and Hearing Manasagangothri...

STUDENT RESEARCH AT A.I.I.S.H. MYSORE

(ARTICLES BASED ON DISSERTATION DONE AT AIISH)

VOLUME V: 2006-2007

PART - A

AUDIOLOGY

Compiled by

Dr. Vijayalakshmi Basavaraj

Director

Dr. Y. V. Geetha

Prof. of Speech Sciences

All India Institute of Speech and Hearing

Manasagangothri, Mysore – 570 006

© 2010

A Publication of the All India Institute of Speech and Hearing

Under the title: “Student Research at A.I.I.S.H Mysore”

Articles based on dissertations done at AIISH: Vol. V

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Published by Dr Vijayalakshmi Basavaraj

Director, AIISH, Mysore

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Foreword

We are happy to bring out the fifth volume of full length articles based on the

dissertation work done by our post graduate students in part fulfillment of their PG degrees in

Audiology and Speech Language Pathology.

This volume includes articles based on dissertations done by the post graduate students

during the year 2006-07. There are totally 38 articles. Part A comprises of 19 papers related to

Audiology which contains articles covering a wide range of topics including evoked potential

testing and related issues; Auditory Processing Disorders; issues related to hearing and aging;

Speech recognition and speech tests; Aids and Appliances for persons with hearing impairment.

Part B comprises of 19 papers in the area of Speech-Language Pathology containing articles

covering various topics in Language and cognition; Aphasia; Motor speech disorders;

Phonological processing; Voice and Fluency disorders. I am glad that our faculty have

enthused the students to undertake research in a variety of topics in Audiology and Speech-

language pathology. The titles of the articles are the titles of the dissertations. The first authors

are the II M.Sc students of 2006-07 and the second authors are their respective guides who

have supervised and guided the research work. The articles reflect the recent research interest

shown by the students in the field of Audiology and Speech-language pathology. The AIISH

faculty members who have guided the dissertations have modified and edited the papers to

bring it to the present shape to the best of their abilities in spite of their busy academic

schedules. Dr. Y.V. Geetha, Professor of Speech Sciences has put in efforts to procure and

compile the edited articles and has herself edited many of the articles. This is highly

appreciated. The unattended mistakes in print and references, if any, in spite of best efforts put

in is regretted.

We hope we will be able to bring out the other volumes of the publications of

dissertation papers pending at the earliest. You may please e mail your valuable feedback about

this volume to [email protected] with the subject “Student research, Volume V A/B,

2006-07”.

Dr. Vijayalakshmi Basavaraj

Director


Table of Contents Sl. No. Title Page No.

1. Speech Identification with Single Channel Multichannel and Channel Free Hearing Aids

Abhay Kumar R & K Rajalakshmi

1

2. Brainstem and Cortical Responses to Speech Stimuli in Individuals with Cochlear Hearing Loss

Anirban Chaudhury & C S Vanaja

11

3. Binaural Amplification – Does Technology Matter?

Anusha R & Manjula P

22

4. Reduction of Stimulus Artifacts in ASSR: An Investigation of a Stimulus Approach

Arivudai Nambi.P & C S Vanaja

33

5. Comparison of Word Recognition Scores using Different Settings of Telecoil in a Digital Hearing Aid

Bijan Saikia & P Manjula

41

6. Estimation of Auditory Thresholds in Cochlear Implant Subjects Using ASSR

Dayal Goswami & Rajalakshmi K

52

7. A search to possible pathways for later peaks of VEMP and N3 potential

Deepashri Agrawal & Animesh Barman

65

8. Acoustic Analysis of the Speech Processed Through Three Amplification Strategies and Their Effect on

Speech Recognition Scores of Individual with Severe Hearing Impairment

Gunjan Chand, Vijayalakshmi Basavaraj & Ajish Abraham

78

9. Some Aspects of Temporal Processing Deficits in Individual with Learning Disability

Kishan M. M & Animesh Barman

93

10. Speech recognition of spectrums with „holes‟ by children

Manasa Ranjan Panda & Asha Yathiraj

104

11. Importance of Long Latency Potential in Pediatric Hearing Assessment

Niraj Kumar & Animesh Barman

114

Pitch perception in individuals with sensorineural hearing loss with and without dead regions

Palash Dutta & K Rajalakshmi

127

12. Development of High and Low Predictable English Sentence Test (Ehlps)

V.V Rahana Nandan & Asha Yathiraj

147

13. NRT: Comparison of Artefact Cancellation and Threshold Estimation Techniques

Shibasis Chowdhury & P. Manjula

158

14. Speech-Evoked Auditory Late Latency Response (ALLR) in hearing aid selection

Shruti Kaul & C.S Vanaja

174

15. Brainstem Responses to Speech in Normal Hearing and Cochlear Hearing Loss Individuals

Sumesh.K & Animesh Barman

187

16. Music Processed by Hearing Aids

Sushmit Mishra & P Manjula

200

17. Efficacy of Frequency Transposition Hearing Aid in Dead Region Subjects

Swapna raj S & K Rajalakshmi

214

18. Effect of Cochlear Hearing Loss on Tone Burst Evoked Stacked Auditory Brainstem Response

Yatin Mahajan & Vanaja C

226

Dissertation Vol.V, Part-A, AIISH, Mysore

1

Speech Identification with Single Channel Multichannel and

Channel-free Hearing Aids Abhay Kumar Roy & K Rajalakshmi

Abstract

Results of investigations in multichannel and single hearing aids are equivocal; this is

due to some acoustical modifications brought about by the multichannel hearing aids. The

present study is aimed to compare the performance of single channel multichannel and channel

free hearing in quiet and two SNR conditions. 12 participants in the age range of 30-60 years

participated in the present study. All the participants had sensory neural hearing loss with

degree ranging from 41-70 dB. Speech identification scores were assessed in quiet and two SNR

conditions (+10 dB and 0 dB SNR) for single, three, eight channel and channel free hearing

aids. Results revealed that participants performed better with channel free hearing aid in quiet

and in presence of noise conditions. The performance was better in 8 channel hearing over three

and single channel only in noise conditions. Results suggest that the new technology overcomes

the disadvantages of multichannel hearing aids. Performance of multichannel hearing aids

showed better performance only in noise but no difference in performance between single and

three channel hearing aids. So increasing the number of channels improves performance only in

noise.

Introduction

The last decade has seen numerous and significant improvements in the technology of

hearing aids. With the advancement of digital technology, digital hearing aids have become

increasingly common. Modern digital signal processing technology includes non-linear,

adaptive, multiple channels/bands, speech enhancement, noise reduction, feedback management

etc. The issue regarding the ideal number of channels has been a hot topic in rehabilitative

amplification over a decade. Despite the ongoing debate, conventional wisdom indicates more

number of channels in digital hearing aid is better and there has seen a surge in the number of

channels in commercially available instruments over the last few years.

Compression is one such technology which helps to optimize the dynamic range of the

individual with hearing impairment. Compression is nothing but a nonlinear amplifier which

automatically adjusts its gain depending upon the incoming signal. Such a signal processing

feature helps to improve the perception in hearing impaired individual by normalizing the

loudness increasing the sound comfort and by reducing the inter-syllabic and inter-phoneme

intensity difference (Dillon, 2001). Although compression technology helps the hearing impaired

Reader in Audiology, All India Institute of Speech and Hearing, Mysore, India

e-mail: [email protected]


2

individual to perceive better, the benefit that compression provides partly depends on the way it

is implemented in hearing aids. Broadly, based on the implementation of number of compression

circuit in the hearing aids, it can be classified into either single channel or multichannel hearing

aids.

In single channel compression the entire dynamic range is optimized across the full range

of frequencies by a single compressor. In multichannel compression hearing aids this dynamic

range is optimized at discrete frequencies by using multiple compressors. Currently, hearing aids

with 1 to 20 channels are commercially available. Over the decades attempts have been made to

investigate if increasing the channel helps the hearing impaired individual to perceive better. It

may appear that the larger the number of channels the better the compensation for individual

hearing impairment. However, increased numbers of channels may also have drawbacks, worthy

of consideration.

Yund and Buckles (1993) measured speech discrimination for 8 channel compression and

linear amplification. As the signal to noise ratio (SNR) decreased the speech identification

became relatively better in multi-channel compared to linear amplification. Yund and Buckles

(1995) reported that speech identification scores improve as the number of channel increases

from 4 to 8 and did not vary significantly between 8 to16 channels. On the contrary, Bustamante

and Braida (1987) reported that multi-channel amplification reduces the speech intelligibility in

hearing impaired individuals. These findings are also supported by Drullman and Smoorenberg

(1997). Hickson (1994) have reported that the performance with 4 channel hearing aid is similar

to that of single channel hearing aid.

Studies have revealed equivocal results about the advantages and disadvantages of

multichannel hearing aid. Relative to single channel compression, multi channel compression

can increase intelligibility because it gives frequency specific amplification which in turn

provides better audibility of speech. Unfortunately, multichannel compression also decreases

some of the essential differences between different phonemes. Because compressor gives less

amplification to intense signals than to weak signals, multichannel compressors tend to decrease

the height of spectral peak and to raise the floor of spectral valleys. That is, they partially flatten

spectral shapes. Spectral peaks and valleys give speech sounds much of their identity. Spectral

flattening makes it harder for the hearing aids users to identify the place of articulation of

consonants (De Gennaro, Braida & Durlach, 1986).

Considering these opposing effects of multichannel compression, it is not surprising that

some experiments have shown multichannel compression to be better than single channel

compression (Kiessling & Steffens, 1991; Moore & Glasberg, 1986, 1988) and some have failed

to show any advantage for multi channel compression (Moore, Peters & Stone, 1998; Plomp,

1976; Walker, Byrne & Dillon, 1984). Multichannels decrease speech intelligibility for normal

hearing people (Hohmann & Kollmeier, 1995; Yund & Buckles, 1995). If high compression ratio

is used in multi channel compression hearing aid, intelligibility is also decreased for hearing

impaired listeners (Bustamante & Braida, 1987; De Gennaro, Braida & Durlach, 1986).


3

Whether the positive effects of multichannel compression outweigh the negative effects

depend on how much audibility is achieved in the reference condition. A net advantage for

multichannel compression is thus least likely for sounds than in the single channel condition.

They are comfortably loud and have been amplified by an appropriate gain frequency response

shape. So, there is a dearth of studies comparing single channel and multichannel compression

and most showing equivocal results. Hence further research is needed in the area to overcome the

ambiguity that is seen in the literature. The emergence of new techniques such as channel free

hearing aids necessitates it to be validated along with the existing techniques such as single

channel and multichannel. Hence current study was undertaken to compare the speech

identification score with the single channel, three channels, eight channels and channel free

hearing aid in quite as well as in two noise conditions (+10 dB SNR and 0 dB SNR).

Method

Present study was designed to compare the hearing aid performance across the channel

in quiet and different noise conditions.

Subjects

Twelve subjects (9 men and 3 women) in the age range of 35 to 60 years (mean age of

48.5) with confirmed diagnosis of sensorineural hearing loss participated in the study. They had

audiometric 3 frequency average (500, 1000 and 2000 Hz) pure-tone thresholds in the range of

41 to70 dB HL with speech identification score of greater than 50%. Tympanometry results

indicated no middle ear pathology. All of them were first time hearing aid users. All the

participants were native Kannada speakers (Language spoken in Karnataka state of India).

Instrumentation

A Calibrated two channel diagnostic audiometer (OB922) was used for estimation of pure

tone thresholds. Calibrated GSI-tympstar middle ear analyzer was used for Immittance

measurements. A single channel (Terra), Three Channel (Cielo), Eight Channel (Syncro),

Channel free (Symbio XT 110) hearing aids were used for the purpose of comparison of

performance. Hearing aids were programmed with NOAH based Connexx 5.3 (Terra and Cielo),

Genie 6 (Syncro) and (Symbio) Oasis plus 7 software. Hearing aids were connected with the

computer using HiPro.

Stimuli were played in laptop 44.1 KHz sampling rate and 32 bit software using

Cyberlink Power DVD Ultra software. Stimuli were routed through the OB922 two channel

audiometer to the two sound calibrated Martin audio C115 speakers.


4

Stimuli

The speech stimuli used in the present study was taken from bi-syllabic word lists in

Kannada developed by Yathiraj and Vijaylakshami (2005). This test contains four word lists,

each with 25 bi-syllabic words, which are phonetically balanced and are equally difficult. All the

four lists were selected for the present study. The words were spoken in conversational style by a

female native speaker of Kannada. They were digitally recorded in an acoustical treated room, on

a data acquisition system using 44.1 KHz sampling frequency and 32-bit analog to digital

converter. All the word lists were mixed with speech babble (Anitha & Manjula, 2005) at +10 dB

and 0 dB SNR. The speech babble is mixed with words with reference to RMS amplitude by

program written in MATLAB 7.

Procedure

Puretone thresholds were obtained using modified Hughson and Westlate procedure

(Carhart & Jerger, 1959) across octave frequencies from 250 to 8000 Hz for air conduction and

250 to 4000 Hz for bone conduction.

Tympanometric measurements were done using 226 Hz probe tone. This was done to

rule out conductive hearing loss due to middle ear pathology. Appropriate probe tips were used

to obtain hermetic seal and comfortable pressure for the subject. The parameters documented

were types of tympanogram and acoustic reflex thresholds agreeing with ear canal volume,

acoustic admittance and the tympanometric peak pressure. The results were also correlated with

the ENT findings.

Hearing aids were programmed on the basis of audiometric thresholds with the default

gain provided by software. Syncro and Cielo had noise management technology. While

programming these noise management options were switched off in order to avoid any unwanted

effect on result. All the hearing aids were switched to Omni directional microphone mode as

there was no need of noise reduction during the testing.

Test was done in acoustically treated room with noise with in permissible limits as per

ANSI (1991) specification. Subjects were seated at distance of one meter and at 45o

azimuths

from the speakers. First the testing was done in unaided condition and later in aided condition. In

the aided condition hearing aids were selected randomly for fitment and testing. Stimuli were

played on a laptop at 44.1 KHz sampling rate with 32 bit operating system and were routed

through the two channel audiometer (OB922). The intensity level was maintained at 40 dBHL

throughout the testing and inter stimulus interval was kept constant at 5 seconds. Written

responses were obtained from the subjects and in case of illiterate subjects the responses were

scored by Kannada speaker.


5

Results

Speech Identification score in Quiet

The speech identification scores of 12 subjects (15 ears) in unaided and aided conditions

are presented in Figure 1. A repeated measure of ANOVA was performed to assess the

significant difference across conditions (unaided & 4 aided conditions). Results showed a

significant difference across conditions (F (4, 39.3) = 14.7, p<0.01). Scheffe Post Analysis of

variance reveled significant difference between unaided condition and aided conditions (p<0.01)

but difference in means across different channel hearing aids data did not reach the significance.

However from the figure it is observed that channel free hearing aid had higher scores compared

to other different channel hearing aids.

Figure1. Speech identification scores in quiet condition

B. Speech Identification Scores in Noise

Figure 2 shows the percentage of speech identification score in quiet, +10 dB SNR and 0

dB SNR conditions for various channel hearing aids (1 channel, 3 channel & 8 channel) and

channel free hearing aid. It can be observed that participants performed better with channel free

and 8 channel hearing aids than single and 3 channel hearing aids in all the conditions (quiet &

+10 dB & 0 dB SNR). Furthermore, it is also clear from the figure 2 that channel free and 8

channel hearing aids show better performance in all the conditions. Participants performed better

with channel free in quiet and 0 dB SNR conditions than 8 channel hearing aid.

Repeated measures ANOVA were performed to assess the significant difference across

hearing aids in quiet and two different SNR conditions. Repeated measures ANOVA revealed

significant main effect of quiet and two SNR conditions (F (1.67, 112) =143.05, p<0.01) but no

significant interaction was observed (F (4.8, 96.6) =0.283, p=0.98). To see the significant

difference across different channel hearing aids and channel free hearing aid, Post Hoc analysis


6

of variance was performed and results revealed the mean difference across different channel

hearing aid and channel free hearing aid did not reach significant difference (p>0.05).

Figure 2: Speech identification scores in quiet and two noise conditions. Open square

indicates Single channel, open triangle indicates three channel and open diamond for channel

free hearing aid.

Discussion

A. Performance in quiet condition

Aided response with different hearing aids is better than in the unaided condition.

Results of the present study revealed no significant difference across hearing aids used in this

study. Although the mean scores did not reach the significance there is difference in mean scores

across hearing aids. Furthermore, more variability in the scores was observed which would have

led to no significant difference across hearing aids. One other reason is the age range studied in

the present study which could have contributed for variability in the scores.

The performance with multichannel hearing aids was almost similar to that observed in

single channel and 3 channel hearing aid. A number of investigators reported no significant

improvement in speech identification by increasing the numbers of channels in multichannel

hearing aid (Louise & Hickson, 1994). Souza, (2002) reported that multichannel hearing aids

with fast compression time constants distort some speech cues, offsetting the benefits of

improved audibility. In the present study, multichannel used syllabic compression, which has fast

attack and release time constants which could have caused the distortion and lead to the much

variability in performance. Anna O‟Brien, (2002) has provided explanation for the poorer

performance observed across studies in multichannel hearing aids. According to her,

theoretically, when vowels, diphthongs and other phonemes are processed by a multichannel

instrument, their key formant sounds may be managed and resolved by different channels,

receiving more or less amplification and compression than was originally present and intended.

This possible outcome distorts relationships among formants and potentially other key features

of vowel, phoneme and word recognition (see Figure-3). As observed in figure 3, an annotation


7

described by Dillon, (2001) shows that in stimulus /ii/ the spectral difference is lost and formant

frequencies are distorted.

In addition, another consideration is that the number of channels, compression ratios and

their time constants (attack and release times) all interact. Taken to an extreme, a large number

of channels with high compression ratios can result in an amplified signal (Plomp, 1988),

stripped of many of the identifiable speech elements. This effect is known as "spectral

smearing." Because of the distorted formant information, spectral smearing is most deleterious to

"place" of consonant articulation (e.g. difficulty discriminating between /b/, /d/ and /g/) and

increases susceptibility to noise (Boothroyd et al, 1996).”

The mean scores of channel free hearing aid were 10% higher compared to other

multichannel and single channel hearing aids. Similar to the present study, Dillon et al., (2003)

showed that the performance of subjects in quiet, impulse noise, for male and female voice was

better with channel free hearing aid compared with multichannel hearing aids. They also showed

that internal noise and distortion seen in the channel free hearing aid is less than those observed

with multichannel hearing aid and that low distortion and less internal noise would have

contributed for the better performance in channel free hearing aid. CASI offers unique frequency

shaping for optimal hearing-loss appropriate frequency response curves. Flexible input-

dependent filter characteristics are applied to the whole signal, allowing frequency-dependent

compression, without splitting the signal into channels and incurring the consequent spectral

smearing potentially present in many-channel instruments.

Sou

nd

Lev

el

S

ou

nd

Lev

el

Fig: 3. Annotated diagram of vowel spectra


8

B. Performance in Noisy condition

Results revealed that mean performance dropped significantly in noise for all hearing

impaired subjects. No significant effect of channel was observed. The drop in performance

across hearing aids may be due to the poorer performance of hearing impaired subjects in

adverse conditions. From Fig. 2 it can be noted that channel free and 8 channel hearing aid

performed better in two noise conditions. In addition, channel free aid provided better

performance in 0 dB SNR condition compared to 8 channel hearing aid. No significant

difference was observed in the present study. This may be due to large variability in data,

because of the small number of subjects and age range studied in the present study (30-68 years).

A number of investigators reported that performance with 8 channel hearing aid is better

than single to 6 channel hearing aids (Yund & Buckle, 1995). More number of channels will

provide the possibility of better fit to the individual hearing impairment. The greater the number

of channels and the narrower the channels, the greater the likelihood that important frequency

components of the signal will fall into channels which do not include higher-intensity

components of the noise of the signal itself. It is important that a signal component has a

positive signal-to-noise ratio (S/N) within a channel because only then can the signal component

determine the amplification in the channel to be amplified appropriately and become useful to

the subject. Whenever the S/N is negative in the channel, the noise controls the amplification and

the signal and noise components are amplified less than would have been appropriate for the

signal component alone. In the multichannel compression haring aids with few broad channels,

however, a signal component may be amplified too little (i.e., "masked electronically") due to the

presence of a noise component which would not have masked it perceptually had the signal and

noise components been amplified appropriately in two separate channel (Stone et. al.,1999).

Although number of studies has shown that multichannel hearing aid performance is

better other group of researchers has shown that there is variability due to sensoryneural hearing

loss (Yund, Simon, & Efron, 1987). It is because of the speech distortions that are caused by the

type of compression and time constants applied in the multichannel hearing aids. That is when

the input signal is broken into channels and applying compression and fast time constants the

spectro-temporal characteristics become distorted and important speech transition information is

lost which has been found to impair speech understanding (Boothroyd et al, 1996). In the present

study also mean scores were higher but there was more variability (SD) indicating not all

subjects improved with 8 channel hearing aid. Lippmann (1978) reported a deterioration of the

scores when the signal was compressed with the noise and Barfod (1978) also obtained

equivalent scores in his study.

Performance of channel free hearing aid was higher with less variability compared to the

multichannel hearing aid. Similar results have been reported by Dillon, (2002). Because, the

channel free hearing aid utilizes recently developed technology, Continuously Adaptive Speech

Integrity (CASI). This strategy offers unique frequency shaping for optimal hearing loss

appropriate frequency response curves. Flexible input-dependent filter characteristics are applied


9

to the whole signal, allowing frequency-dependent compression, without splitting the signal into

channels and incurring the consequent spectral smearing potentially present in many-channel

instruments. CASI analyses incoming signals according to their intensity and dominant spectral

elements and calculates the corresponding gain characteristic to be applied. Spectral

characteristics of speech are maintained resulting in more "natural" sounding amplification. So

the reduced spectral smearing and frequency dependent compression would have improved the

performance of subjects with channel free hearing aid.

One important observation made in the study was that channel free hearing aid showed

better performance over the eight channel hearing aid in 0 dB SNR and quiet condition. There

was no difference in performance between eight channel and channel free hearing aid in 10 dB

SNR. Bear and Moore (1993) and Ter Krause (1993) have shown no effect of spectral smearing

on speech identification scores in normal hearing subjects in quiet but it has significant effect in

adverse conditions. They further said that poor frequency resolution observed in cochlear hearing

loss subjects affects identification scores in noise rather in quiet. From the above it is understood

that in the adverse conditions (like 0 dB SNR) the amount of spectral information utilized for

understanding speech is more compared to the conditions like 10 dB SNR and quiet conditions.

In the multichannel hearing aids there is temporal distortion and spectral smearing. Small

improvement observed for channel free hearing aid may be due to the reduced spectral smearing

and temporal distortions which would have affected the speech identifications scores in

multichannel hearing aids.

To conclude, performance of subjects with channel free hearing aid was better in quiet

and noise conditions. Performance of multichannel hearing aids showed better performance only

in noise but no difference in performance between single and three channel hearing aids. So

increasing the number of channels improves performance only in noise.

References

Bentler, R. A. & Duve, M. R. (2000). Comparison of hearing aids over the 20th century. Ear and

Hearing, 21, 625-639.

Boike, K.T. & Souza, P.E. ( 2000a). Effect of compression ratio on speech recognition and.

speech-quality ratings with wide dynamic range compression amplification. J Speech

Language and Hearing Research, 43, 456-468.

Boike, K.T. & Souza, P.E. ( 2000b). Effect of compression ratio on speech recognition in

temporally complex background noise. Presented at the International Hearing Aid

Conference, Lake Tahoe, CA.

Bustamente, D. K. & Braida, L. D. (1987). Multiband compression limiting for severely

impaired listeners. Journal of Rehabilitation Research and Development, 24, 149-160.

Hickson, L. M. H. (1994). Compression amplification in hearing aids. American Journal of

Audiology, 3, 51-65.


10

Hohmann V. & Kollmeier B. (1995). The effect of multichannel dynamic compression on speech

intelligibility. Journal of Acoustic Society of America 97, 1191-1195.

Kiesseling, J. & Steffens, T. (1991). “Clinical evaluation of a programmable three channel

automatic gain control amplification system.” Audiology, 30(2), 70 – 81.

Moore, B. C. J. & Glasberg, B. R. (1986). A comparison of two-channel and single-channel

compression hearing aids. Audiology, 25, 210-226.

Moore, B. C. J., Alcantara, J. I., Stone, M. A. & Glasberg, B. R. (1999). Use of a loudness model

for hearing aid fitting: II. Hearing aids with multi-channel compression. British Journal

of Audiology, 33, 157-170.

Moor, B. & Glasberg, B. (1998), “A comparison of four methods of implementing automatic

gain control (AGC) in hearing aids,” British journal of Audiology, 22(2), 93 – 104.

Plomp, R. (1988). The negative effect of amplitude compression in multichannel hearing aids in

the light of the modulation-transfer function. Journal of Acoustic Society of America, 83,

2322-2327.

Souza, P. E. & Turner, C. W. (1999). Quantifying the contribution of audibility to recognition of

compression-amplified speech. Ear and Hearing, 20, 12-20.

Stelmachowicz, P. G., Kopun, J., Mace, A. & Lewis, D. (1995). The perception of amplified

speech by listeners with hearing loss: Acoustic correlates. Journal of Acoustic Society of

America, 98, 1388-1399.

Stone, M. A., Moore, B. C. J., Wojtczak, M. & Gudgin, E. (1997). Effects of fast-acting high-

frequency compression on the intelligibility of speech in steady and fluctuating

background sounds. British Journal of Audiology, 31, 257-273.

Yund, E. W. & Buckles, K. M. (1995b). Multichannel compression hearing aids, Effect of

number of channels on speech discrimination in noise. Journal of Acoustic Society of

America, 97, 1206-1223.

Yund, E.W. & Buckles, K. M. (1995a). Enhanced speech perception at low signal-to-noise ratios

with multichannel compression hearing aids. Journal of Acoustic Society of America, 97,

1224-1240.


11

Brainstem and Cortical Responses to Speech Stimuli in Individuals

with Cochlear Hearing Loss

Anirban Chaudhury & Vanaja C S

Abstract

This study investigated the effect cochlear pathology on brainstem and cortical responses

to speech burst and transition. The relationship between these potentials and speech

identification scores was also investigated. Ten adult subjects with cochlear pathology and 12

age matched normal hearing subjects were included in the study. Burst and transition portions

were extracted separately from the stimuli /pa/, /ta/, /ka/. Burst evoked brainstem responses were

analyzed for wave V, transient evoked brainstem responses were analyzed for peak V, A, C, D, E

and F and cortical evoked potentials were analyzed for P1, N1, P2 and N2. Speech identification

scores in quiet and in the presence of noise were obtained for bisyllabic word list in Kannada.

Burst evoked responses showed a significant difference between the latency of wave V obtained

in subjects with cochlear hearing loss and those with normal hearing group but no significant

difference was found in terms of wave V amplitude. For the transition stimuli, latencies of wave

V, A, C, D, E, and F as well as the amplitude of wave V were significantly different between the

two groups. All the components (V, A to F) evoked by transition stimuli significantly correlated

with SIS scores in noise. But no correlation was observed for burst evoked brainstem responses.

There was no significant difference between groups for all the components of LLR (P1, N1, P2 &

N2) but N1-P2 amplitude was significantly different between the groups. These findings suggest

that cochlear hearing loss impairs the processing of the burst and transition portion of speech

signal mainly at the brainstem level.

Introduction

Individuals with sensorineural hearing loss have difficulty in understanding speech

(Glasberg & Moore, 1989). Behavioral tests have been devised and used to assess these speech

processing difficulties. But these types of behavioral tests cannot be used in some of the difficult-

to-test population. In such individuals objective electrophysiological tests may be helpful in

predicting speech perception.

Conventionally brief acoustic signals such as clicks, tone bursts and tone pips have been

used to elicit the ABR. Recent investigations have shown that brainstem responses to speech

stimuli can also be reliably recorded and analyzed (Khaladkar, Karthik & Vanaja, 2005). As

brainstem responses can be best recorded using short duration signals, burst or transition portion

Professor of Audiology, School of Audiology and Speech Language Pathology, Bharathiya Vidya Peet University,

Katra-Dhanakawadi, Pune, India. e-mail: [email protected]


12

have been used to elicit brainstem responses in these studies. The speech-evoked ABR recorded

in human brainstem can be divided into transient and sustained portions, specifically the onset

response and the frequency-following response (FFR) (Kraus & Nicol, 2005). Onset responses

are transient, similar to click evoked ABR with peak durations lasting tenths of milliseconds.

The FFR arises from the harmonic portion of the stimulus and is characterized as a series of

transient neural events phase locked to periodic information within the stimulus (Batra, Kuwada

& Maher, 1986). Galbraith, Arbagey, Branski, Comerci and Rector (1995) demonstrated that the

FFR elicited by word stimuli reflects the stimulus accurately enough to allow it to be recognized

as intelligible speech when “played back” as an auditory stimulus. More recently, Galbraith,

Amaya, Rivera, Donan, Duong and Hsu, (2004) have suggested that based on the FFR pattern of

activation for forward and backward speech, synaptic processing at the level of the brain stem is

more effective for forward speech stimuli characterized by highly familiar prosodic and

phonemic structure than to backward speech. The studies carried out on children with learning

disability have shown that responses to speech stimuli were deviant in these children even when

responses to nonspeech stimuli were normal (Khaladkar, 2005).

Khaladkar, Karthik and Vanaja (2005) obtained speech burst ABRs for 20 ears with mild

to moderate sensorineural hearing loss. Two stimuli were used to evoke the ABR; a standard

acoustic click and the burst portion of the syllable /t/. The result of their study indicate that while

click evoked ABRs exhibited latency values within normal limits, speech burst evoked ABRs

showed more deviant results. There was a significant correlation between speech identification

score and speech burst ABR, perhaps suggesting that using speech sounds to elicit the ABR

offers an opportunity to better isolate normal speech processing from abnormal speech

processing. Hedrick and Jesteadt (1996) reported that sensorineural hearing loss may disrupt

formant transient coding or any type of dynamic process in periphery (i.e. rapidly changing

aspects of speech signal is not being coded). So it can be hypothesized that the transition

responses evoked by ABR may provide useful information about processing of speech at

brainstem level. There was also a need to study the cortical representation of burst and transition

of speech stimuli in subjects with normal hearing and those with hearing loss.

Speech evoked LLR were frequently used to study the neural representation of speech

sound in populations with impaired speech understanding. The underlying assumption is that

speech perception is dependent on the neural detection of time-varying spectral and temporal

cues contained in the speech signal (Tremblay, Billings & Rohila, 2004). The P1-N1-P2

complex reflects the neural detection of time-varying acoustic cues. Because abnormal P1-N1-

P2 response patterns have been reported in children and adults with varying types of speech

perception impairments, there is a current surge of interest in learning more about this brain-

behavior relationship (Rance, Wesson, Wunderlich & Dowell, 2002). There is a dearth of

studies correlating both brainstem and cortical responses with SIS in subjects with SN hearing

loss. Also research has not been carried out to study the cortical responses for only burst or

transition portion of a syllable. Hence the present study aimed to investigate if there is a


13

difference between subjects with normal hearing and those with cochlear pathology in the

following responses:

Brainstem responses to speech burst

Brainstem responses to transition of speech

Cortical responses to speech burst

Cortical responses to transition of speech

The study also investigated the relationship between the following in subjects with cochlear

pathology:

Brainstem responses to speech burst and speech identification scores

Brainstem responses to transition of speech and speech identification scores

Cortical responses to speech burst and speech identification scores

Cortical responses to transition of speech and speech identification scores

Method

Participants:

Participants of the present study were divided into two groups. Control group included

twelve ears of normal hearing individuals aged 15-50 years and hearing sensitivity within 15

dBHL. The clinical group included twenty two ears with cochlear hearing loss of subjects aged

15-50 years with hearing sensitivity within 55 dBHL. The hearing impairment was post-lingual.

Participants had no history of speech and language problem and all of them were native speakers

of Kannada.

Instrumentation:

A calibrated dual channel OB922 clinical audiometer (Version 2) with TDH 39

earphones housed in MX/41 AR ear cushions and Radio ear B 71 bone vibrator was used for

estimating pure tone threshold and speech audiometry. A calibrated GSI Tympstar middle ear

analyzer was used for tympanometry and acoustic reflex measurement to rule out middle ear

pathology. The IHS smart EP, version 2.39 (Intelligent Hearing systems, Florida, USA) with

Eartone 3A insert earphones was used to record and analyze auditory evoked potentials.

Materials:

Extracted transition and burst portion of naturally produced syllable /pa/, /ta/, /ka/ by an

adult female Kannada speaker was used to elicit brainstem and cortical response. The syllables

were spoken into a unidirectional microphone connected to the computer. To view and edit the

speech sounds, PRAAT (version 4.4.27) was used. The wave file was then converted to stimulus

file for ALLR recording using „Stim conv‟ provided by the Intelligent Hearing System (version

2.39). All the stimuli were calibrated in dB nHL. Paired words in Kannada were used to


14

determine the Speech Reception Thresholds (SRT) and recorded version of the word list from

speech identification test in Kannada developed by Vandana (1998) was used to determine SIS.

Test procedure:

Pure tone thresholds were assessed using modified Hughson Westlake method (Carhart &

Jerger, 1959) for air conduction stimuli from 250 Hz to 8000 Hz and for bone conduction stimuli

from 250 Hz to 4000 Hz. Speech Reception Threshold (SRT) was obtained using paired words in

Kannada. Speech identification scores (SIS) were obtained at 40 dB SL (ref: SRT) in both quiet

and noise (speech babble, 0 dB SNR) with PB word list developed by Vandana (1998). All the

auditory evoked potentials were recorded using conventional electrode montage with the

noninverting electrode on vertex, inverting electrode on mastoid and common electrode on the

forehead. Stimuli were presented at 40 dBSL (ref. SRT). Repetition rate of the stimuli was

11.1/sec for brainstem responses and 3.1/sec for cortical responses. The analysis window was 20

ms for brainstem responses to burst, 50 ms for brainstem responses to transition and 300 ms to

cortical responses. The analysis included 50 ms pre stimulus window while recording cortical

responses. Responses for 1500 stimuli were filtered using a band pass filter of 100 Hz to 3 KHz

and amplified 100 K times for brainstem responses. Cortical responses for 300 stimuli were

filtered using a band pass filter of 1-30 Hz and amplified 50 K times.

Results

Wave V and its negative trough (wave A) of ABR evoked by burst were marked. The

peak to trough amplitude of the wave V was measured. Similarly the Vth peak for transition

evoked ABR was also identified and amplitude was measured. In addition since transition ABR

has a steady state portion FFR was also analyzed as described by Kraus (2000). For the transition

evoked ABR latency of wave V, wave A, C, D, E and F and amplitude of wave V were

considered. For LLR, peak P1, N1, P2 and N2 were measured. The data obtained were tabulated

and statistical analyses were carried out using SPSS software (V15, SPSS Inc).

1. Latency and amplitude of wave V in individuals with normal hearing and individuals

with cochlear hearing loss for burst evoked ABR

Table 1 Shows the mean latency and amplitude of wave V evoked by bursts of /pa/, /ta/

and /ka/ in individuals with normal hearing and those with cochlear hearing loss. It can be noted

from the table that latency of wave V for /p/ and /k/ was similar but /t/ latency was shorter in

both the groups. The amplitude of the /p/ and /k/ was similar but /t/ amplitude was lesser than /p/

and /k/ in both the groups. It can be observed from the table that the latency was longer and

amplitude was lesser in individuals with hearing impairment than that of normal hearing, for all

the stimuli.

Multivariate Analysis of Variance was administered to assess the effect of groups and

three stimuli on latency and amplitude for wave V. Results revealed that there was a significant

effect of cochlear hearing loss on latency (p<0.05) but there was no significant difference in


15

amplitude of wave V between the groups (p>0.05). Also there was no interaction of stimulus

with group for latency and amplitude. Scheffe‟s post hoc showed no significant effect of

stimulus on latency and amplitude of wave V in both groups.

Table-1: Mean and SD of latency and amplitude of wave V

Group pa ta ka

Latency

in msec

Amplitude

in µv

Latency

in msec

Amplitude

in µv

Latency

in msec

Amplitude

in µv

Normal hearing 7.1 (0.5) 0.44 (0.04) 6.2 (0.4) 0.4 (0.2) 7.4 (0.7) 0.5 (0.3)

Hearing impairment 7.2 (0.02) 0.38 (0.8) 6.99 (0.7) 0.35 (0.1) 7.7 (1.6) 0.4 (0.2)

2. Latency and amplitude of peaks in individuals with normal hearing and individuals with

cochlear hearing loss for transition evoked ABR and FFR

Table 2 shows the mean latency of peaks V, A, C, D, E, F and amplitude of peak V,

elicited by transition portion of /pa/, /ta/ and /ka/ in individuals with normal hearing and hearing

impairment. For individuals with normal hearing the latency of wave V for /pa/ and /ka/ was

similar but /ta/ latency was longer than the other two stimuli. The amplitude of the /k/ was higher

than /t/ and /p/. However, the standard deviation for amplitude of /k/ was larger indicating

greater variability. For individuals with hearing impairment the trend obtained for different

stimuli was similar to that observed for participants with normal hearing. The latency of wave V

for /pa/ and /ka/ was similar but /ta/ was longer than the other two stimuli. However, the

amplitude of the /pa/ and /ka/ was similar but /ta/ amplitude was lesser than /pa/ and /ka/ in this

group.

Table-2: Latency of wave V, A, C, D, E, F and amplitude of wave V in individuals with normal

hearing and hearing impairment

Subjects

and

Stimuli

V A C D E F

Latency

in msec

Amplitude

in µv

Latency

in msec

Latency

in msec

Latency

in msec

Latency

in msec

Latency

in msec

norm

al

hea

ring

pa 9.9 (2.3) 0.3 (0.04) 11.1 (2.3) 13.8(2.7) 17.2(3.09) 21.4 (3.1) 25.6 (3.2)

ta 12.5 (1.6) 0.3 (0.07) 13.66 (1.8) 18.3 (2.7) 21.9 (2.9) 25.5 (3) 29.8 (3.3)

ka 9.8 (2.4) 0.39 (0.2) 11.5 (2.4) 14.8 (1.7) 18.3 (1.5) 22.4 (1.6) 26.8 (1.6)

hea

ring

impai

red

pa 15.4(2.5) 0.2(0.07) 17.2(2.9) 22.1(2.66) 25.7(2.6) 30.9(3.4) 35.1(3.6)

ta 19.6(1.3) 0.22(0.2) 21.7(1.6) 27.3(2.0) 31.4(2.0) 36(1.3) 40.4(1.6)

ka 16.2(1.7) 0.28(0.2) 18.1(1.9) 22(1.4) 26.6(2.0) 30.9(1.9) 35.2(1.8)

Multivariate analysis of variance was administered to assess the significant difference

between groups for three stimuli in latency and amplitude. There was a main effect of group

(cochlear hearing loss) on latency of all the peaks and amplitude of wave V (p<0.01) and there

was no interaction between stimulus and group. Scheffe‟s Post Hoc analysis of variance revealed


16

that the amplitude and latency of /ta/ differed significantly from that of /pa/ and /ka/ (p<0.01) for

wave V of ABR and other waves of FFR but there was no significant difference between /pa/ and

/ka/ (p>0.05).

3. Long latency responses evoked by speech bursts

Table 3 shows the mean for latencies for the components (P1, NI, P2, N2) of LLR and

amplitude of NI-P2 complex in individuals with normal hearing and individuals with cochlear

hearing loss across three speech burst stimuli. Multivariate analysis of variance was carried out

to check if there is a main effect of cochlear hearing loss on latencies of components of LLR and

N1-P2 amplitude. Results revealed that there was no significant main effect of group (cochlear

hearing loss) for its measure on latency of all the peaks (p>0.05) but N1-P2 amplitude differed

significantly (p<0.01) and no interaction was observed between stimulus and group.

Table 3: Mean (SD) of Latency for components of LLR and N1-P2 amplitude recorded with

burst in individuals with normal hearing and hearing impairment

P1 N1 P2 N2 N1P2 amp

Individuals

with

normal

hearing

pa 86.7(13.8) 127.2(12.3) 188.2(14.7) 197.6(24.1) 1.3(0.3)

ta 82.3(8.3) 128.4(16.7) 181.8(14.09) 229.2(11.8) 1.5(0.4)

ka 86.9(18.6) 130.7(12.4) 187.1(25.4) 225.4(20.5) 1.3(0.5)

Individuals

with

hearing

impairment

pa 87.3(34.2) 127.12(37.93) 184.65(42.06) 235.42(43.52) 0.98(0.17)

ta 83.3(22.7) 121.32(17.99) 173.25(16.19) 230.02(11.13) 0.83(0.16)

ka 86.07(21.90) 123.2(25.80) 177.47(17.91) 233.42(13.06) 1.04(0.30)

4. Long latency responses evoked by formant transition

Table 4 shows latencies for the components (P1, NI, P2, N2) of LLR and amplitude of

NI-P2 complex in individuals with normal hearing and individuals with cochlear hearing loss

across three speech formant transitions. Multivariate analysis of variance was carried out to

check if there was a main effect of cochlear hearing loss on latencies of P1, N1, P2, N2 and

amplitude of N1-P2.

Table 4: Mean and SD of latency (in ms) and amplitude (in µ V) of LLR peaks elicited by transition

P1 latency N1 latency P2 latency N2 latency N1P2 amp

Normal

hearing

subjects

pa 92.75(15.24) 139.31(2) 194.46(24.83) 251.31(21.29) 1.07(0.34)

ta 95.6(24.82 142.91(29.02 212.12(48.43 240.36(36.17) 1.33(1.33)

ka 97.1(9.88) 143.19(13.07) 211.94(31.01) 242.94(32.91) 1.47(0.4)

Hearing

impaired

subjects

pa 90.82(25.92) 123.52(24.82) 176.10(31.82) 230.85(44.91) 0.94(0.17)

ta 86.62(25.53) 119.87(23.95) 178.57(35.64) 227.92(41.21) 1.01(0.16)

ka 96.3(19.11) 137.07(19.66) 202.12(10.06) 257.4(15.99) 1.04(0.22)


17

Results revealed that there was no significant main effect of cochlear hearing loss (p>

0.05) and no interaction was observed between group and stimulus. Sheffec‟s Post Hoc analysis

revealed no significant effect of stimulus on latency or amplitude of LLR.

5. Speech identification scores in individuals with normal hearing and individuals with

cochlear hearing loss

Table 5 shows the speech identification scores in quiet and in presence of noisy condition

for the participants with normal hearing and those with hearing impairment. Independent sample

t test revealed that there was a significant difference between the scores of participants with

normal hearing and with hearing impairment in both quiet (t =13.0, p<0.01) and noisy condition

(t=19.9, p<0.01).

Table 5: Mean (SD) of speech identification scores in quiet and in the presence of noise

Group In Quiet In Noise

Normal Hearing 100 97 (3.9)

Hearing Impaired 76.2 (6.4) 15.6 (13.4)

6. Relationship between speech identification scores and brainstem and cortical responses

Pearson product moment correlation analysis was carried out to check the relationship of

latency and amplitude of brainstem potentials for the three stimuli with speech identification

scores (SIS) in quiet and in the presence of noise. Results revealed that SIS in noise correlated

significantly with formant transition evoked FFR and wave V for all the three stimuli (refer

Table 6 for r values) but SIS score in quiet did not show a significant correlation. Speech burst

evoked ABR and LLR as well as transition evoked LLR did not show a significant correlation

with SIS scores in quiet or in the presence of noise.

To summarize the results of the present study revealed that brainstem and cortical

responses to bursts and transition of speech stimuli can be recorded from participants with

normal hearing as well as those with hearing loss.

Table 6: Correlation of SIS scores with brainstem responses evoked by transition of /pa/, /ta/ and /ka/

Latency &

Amplitude

pa ta ka

In quiet In noise In quiet In noise In quiet In noise

V latency -0.217 -0.740** -0.281 -0.896** -0.235 -0.813**

V amplitude 0.286 0.640** 0.129 0.491 0.190 -0.251

A latency -0.293 -0.728** -0.394 -0.909** -0.287 -0.778**

C latency -0.325 -0.726** -0.341 -0.862** -0.397 -0.829**

D latency -0.288 -0.630** -0.354 -0.867** -0.413 -0.829**

E latency -0.303 -0.644** -0.365 -0.862** -0.416 -0.837**

F latency -0.368 -0641** -0.345 -0.845** -0.387 -0.820**

*p<0.05 and **p<0.01


18

There was a significant effect of hearing loss on brainstem responses to speech but

cortical responses to speech were not affected by hearing loss. Speech identification scores

obtained in the presence of noise showed a significant correlation with wave V and FFR evoked

by transition of speech.

Discussion

In the present study brainstem responses and cortical responses could be recorded for all

the stimuli from all the participants with normal hearing as well as those with mild to moderate

hearing loss. The latencies of peak V for different stimuli obtained in the present study are

comparable with those reported by Reddy, Kumar and Vanaja (2004) except for /ka/ which had

longer latency in the present study. This could be due to the difference in the stimuli used in the

two studies. The duration of the signals used in the present study was longer than those used by

the earlier study and the difference was largest for /ka/. ABR is an onset response and the latency

and amplitude of the response depends on stimulus onset/rise time, spectrum of the response and

the duration of the signal (Gorga et al., 1984). Differences in latencies can be attributed to the

differences in spectrum, rise time of the stimulus and durational differences of the stimuli used in

the two studies.

The prolongation of latencies in subjects with hearing impairment may be due to the

overall reduction in audibility. Previous studies on click evoked ABR have also reported that the

latency of all the peaks increase with increase in hearing threshold (Oates & Stapells, 1992).

Though statistically not significant the mean amplitude was lesser in subjects with hearing

impairment when compared to those with normal hearing. This is probably due to reduction in

number of nerve fibers responding for the stimuli. It has been reported in literature that the

amplitude of ABR depends on the number of nerve fibers firing (Hecox, Squires & Galambox,

1976). Thus the results of the present study suggest that coding of the processing of burst is

effected in subjects with hearing impairment. However, speech identification scores in quiet or in

the presence of noise did not show a significant correlation with latency or amplitude of ABR

elicited by burst. These results contradict the report of Khaladkar, Karthik and Vanaja (2005)

who observed that there was a significant correlation between SIS and speech burst ABR in

subjects with sensorineural hearing loss.

The latency of the onset response (Wave V and A) for the transition portion of the signal

in the present study was longer than that reported by King, Warrier, Hayes and Kraus (2002) but

the latency for the other peaks (C, D, E and F) was shorter. It has been reported that the wave V

and A signal the onset of sound at the brainstem whereas wave C is the response to the onset of

the vowel (Kraus & Nicol, 2005). The other peaks, D, E and F are responses to sustained portion

of the signal. So probably the difference in latency reflects the difference in the stimulus used in

the two studies. King, Warrier, Hayes and Kraus (2002) used synthesized transition of /da/ with

40 msec duration. On the other hand in the present study a natural stimulus was taken and the

transition part was extracted. The duration of transition in the present study was around 25 msec


19

for /pa/, 49 msec for /ta/ and 41 msec for /ka/. The fundamental frequency ranged from 103 to

121 Hz in their study and it was around 230 Hz in the present study.

The latency of the FFR portion in hearing impaired subjects was prolonged compared to

normal hearing subjects and the amplitude was significantly reduced in these subjects. This

suggests that the encoding of the sustained portion was affected in the participants with hearing

impairment. The inter-peak latency difference between D and E as well as E and F were around 4

msec in subjects with normal hearing whereas it was around 5 msec in subjects with hearing loss.

This indicates that processing of the fundamental frequencies was affected in subjects with

hearing impairment. It has been reported in literature that the F0 and F1 coding are affected in

persons with hearing impairment at the brainstem level and this is reflected in the abnormalities

in the waveform of ABR (Kraus & Nicol, 2005).

Auditory system encodes the F0 from fine structure but it can also encode the F0 from the

envelope but encoding of F0 from the envelope is weaker when compared to that extracted from

the fine structure (Zeng et al., 2004). In addition psycho-acoustical studies have shown that

cochlear hearing impaired subjects are impaired in coding the temporal fine structure of the

speech signal which contains the F0 and harmonics (Lorenzi, Gilbert, Carn, Garnier & Moore

2006). This indicates a greatly reduced ability to use temporal fine structure speech in

individuals with moderate hearing loss. This loss of ability to use temporal fine structure

information perhaps was related to a loss of neural synchrony (Woolf, Ryan & Bone, 1981). This

would have contributed for reduced amplitude and prolonged latencies in subjects with cochlear

hearing loss.

The recent studies have shown that speech in quiet could be completely understood with

only envelope cues (amplitude variation of the speech signal) (Nambi, Mahajan, Narne &

Vanaja, 2007). But understanding of speech in noise depends on the encoding of the fine

structure of the speech signal as well as envelope. It has been reported that coding of envelope of

the speech signal is normal in cochlear hearing loss subjects but processing of temporal fine

structure is impaired. The results of correlation also revealed that SIS scores in noise were

correlated well with components of FFR. This supports the hypothesis that processing of

temporal fine structure is affected in subjects with cochlear hearing loss.

There is dearth of study investigating LLR with burst and transition in subjects with

hearing loss. However the results obtained in this study are comparable with those reported in

literature for other stimuli. There was no significant difference in latency of LLR for the

participants with normal hearing and those with hearing impairment. This may be because the

degree of hearing loss was less than moderate degree. Mild to moderate degree of hearing

impairment do not significantly influence the latency of LLR (Albera et al., 1991). It has been

reported that at suprathreshold levels the latency of LLR is not significantly affected by intensity

of the stimulus (Picton et al., 1978). Variability of the LLR latency in normal subjects is also

high. This may have been one of the reasons for obtaining no significant difference in the latency

of LLR in the two groups. The N1-P2 amplitude was significantly better in subjects with hearing


20

loss when compared to that of normal hearing subjects. This suggests that probably less number

of cortical cells were responding in subjects with hearing loss. It has been reported that the

amplitudes of LLR depends on the number of cells responding for the stimulus and that long

deprivation of auditory stimuli may lead to loss of cells at the cortical level (Polley, Chen-Bee &

Frostig, 1999). However, the duration of hearing impairment in a majority of subjects in the

present study was not more than 9 months. Probably there would have been a significant effect

on LLR if the duration of hearing impairment was more. No significant correlation between SIS

and LLR measures suggests that probably the poor speech perception in the subjects was mainly

due to abnormal encoding of speech at the cortical and brainstem level.

Conclusion

In this study there was a significant difference in burst evoked wave V latency between

cochlear hearing loss group and normal hearing group but no significant difference was found in

terms of wave V amplitude. For the transition stimuli, latencies of wave V, A, C, D, E & F and

amplitude of wave V were significantly different between the two groups. All the components

(V, A to F) evoked by transition stimuli significantly correlated with SIS scores in noise. But no

correlation was observed for burst evoked brainstem responses. There was no significant

difference between groups for all the components of LLR (P1, N1, P2 & N2) but N1-P2

amplitude was significantly different between groups. No correlation found with SIS in quiet as

well as in noise. It can be concluded from the results of the present study that cochlear hearing

loss impairs the processing of the burst and transition portion of speech signal.

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21

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22

Binaural Amplification – Does Technology Matter?

Anusha & Manjula P

Abstract

Hearing impairment is a reduction in the hearing sensitivity which will cause

deterioration in the speech abilities (Stach, 1997). Hearing aids, in particular, binaural

amplification are useful in the restoration of speech perception, in addition to perception of

environmental sounds, promoting improvement in communication skills according to Markides

(1977). The present study aimed at comparing the performance of the individuals with hearing

loss, in terms of improved audibility, understanding and quality of speech using binaural analog

hearing aids (AA), binaural digital hearing aids (DD), binaural amplification with analog and

digital hearing aids in opposite ears (AD). Results indicated no significant difference between

the DD and the AD conditions though the mean performance in the DD condition was higher

than that of the AD condition, for both the SRS and the quality rating of speech. It is implied

from the present study that the individuals with hearing impairment can be suggested to use

analog hearing aid in one ear and digital hearing aid in the opposite ear till they can afford for

binaural digital hearing aids considering the expensive nature of the digital hearing aids.

Key words: Analog hearing aids, digital hearing aids, speech recognition scores, quality rating

of speech, processing delay

Introduction

The problems caused by cochlear or sensory hearing impairment may be ameliorated

with the use of hearing aids. When compared to unaided hearing, hearing with amplification can

increase the amount of relevant information reaching through listener‟s speech recognition

system. As a primary management tool, amplification aims to raise the input signal level

sufficiently to activate the residual hearing while keeping the intensity within comfort range. It

also aims to shape the amplified signal to provide appropriate gain at each frequency in

accordance with the pattern of the deficit. Further, it should provide the best quality of sound for

different acoustic environments.

Amplification can not restore the lost capacity but it can help minimize the usefulness of

residual hearing (Sanders, 1977). There are different types of hearing aids, analog and digital,

depending on the technology they use to process the signal. The so called digital hearing aids are

an outgrowth of the computer revolution that has transformed our society (Ross, 1997). The

digital signal processing used in a digital hearing aid provides a better speech performance,

Professor in Audiology, All India Institute of Speech and Hearing, Mysore, India



23

hearing levels, noise reduction mechanism, feed back suppression, etc., compared to the analog

hearing aids (Markides, 1977).

The analog amplification schemes had already reached a high level of sophistication

before the digital technology was introduced. Nonetheless, the major benefits from the digital

hearing aids are not to be underestimated. Also, as the technology improved, the cost of the

hearing aid using digital technology also increased. Effective use of hearing aids depends on the

optimal fitting. It should be ensured that the individuals with hearing impairment are given

adequate opportunity to become sophisticated users of amplification (Sanders, 1982).

Now that the technology has improved so much it is considered worthwhile fitting the

amplification in both ears namely binaural amplification (Sanders, 1993). Unless there are

specific contra-indications for fitting both the ears, every candidate for hearing aid with bilateral

hearing loss should be considered a candidate for binaural amplification. It should be considered

a dis-service to individuals with hearing impairment with two usable ears to make only a

monaural recommendation (MacKeith & Coles, 1971). Binaural performance is researched to a

greater extent due to the advantage of binaural amplification (Nabelek & Robinson, 1982). It is

essential that we educate the individuals with hearing impairment about the new technological

advancements so that they can decide about purchasing new hearing aids that might improve

listening (Sanders, 1993).

Even though the digital hearing aids have been commercially available since 1995 (Hirsh,

1995), its high cost reduces the number of seekers especially when the issue is about providing

amplification for both the ears. Some of them are ready to use a digital hearing aid in one ear and

analog hearing aid in the other till they can afford for binaural digital hearing aids. Condie,

Scollie and Checkly (1984) studied the performance of speech of children and concluded that the

performance with binaural digital hearing aids was better compared to binaural analog hearing

aids. Also, a significant improvement in speech perception in quiet and in noise was noticed.

This study focuses on the performance of individuals with hearing impairment while using one

digital and one analog hearing aid in opposite ears.

The aim of the present study was to compare the performance of the individuals with

hearing loss, in terms of improved audibility, understanding and quality of speech using:

1. binaural analog hearing aids

2. binaural digital hearing aids

3. binaural amplification with analog and digital hearing aids in opposite ears

Method Participants

The data from 15 participants were collected. The participants gave informed consent and

fulfilled the following selection criteria:

Age range from 16 to 60 years (mean = 49.06 years)


24

first time hearing aid users, native and fluent speakers of Kannada

Bilateral moderate to moderately severe (PTA = 41 to 70 dBHL) symmetrical (<20dB difference

between the PTA of right and left ears) sensorineural hearing loss

Equipment

The following instruments were used:

1. A calibrated sound field audiometer for unaided and aided testing.

2. A CD player connected to the audiometer for playing the speech material.

3. Two digital Behind-The-Ear (BTE) hearing aids and two analog hearing aids with a fitting range

to suit the hearing loss of the participants. Appropriate sized ear tips to fit the ears of the

participants.

4. Hipro and a personal computer with a soft ware to program the digital hearing aids

5. Calibrated hearing aid test system to measure the Real Ear Insertion Gain (REIG).

6. Calibrated hearing aid test system for measuring group delay of the hearing aids.

Speech Material Used

1. Four lists of Phonemically Balanced Kannada words developed by Yathiraj and

Vijayalakshmi (2006) were used for measuring Speech Recognition Scores. Each list

consists of 25 words. All the four lists were recorded using an adult female voice with

normal vocal effort.

2. A standard passage in Kannada was used for rating the quality of speech through the

hearing aid combinations. The passage contained all the speech sounds of the language.

The sample (one minute and twenty seconds) was recorded by an adult male voice with

normal vocal effort.

Test Environment

The test was conducted in a sound treated environment with ambient noise levels within

permissible limits.

Procedure

The testing procedure consisted of five phases

1. Pre-selection and programming of the hearing aids

2. Measurement of the insertion gain for hearing aid selection

3. Establishing the Speech Recognition Scores (SRS) using various combinations of the

selected hearing aids

4. Quality rating of each combination of the selected hearing aids

5. Group and phase delay measurement

Phase 1: Pre-selection and programming of hearing aids

Commercially available two digital and two analog BTE hearing aids were selected with

the fitting range to suit the hearing loss of the participants. The digital hearing aid was connected


25

through a Hipro to the Personal Computer (PC) with software for programming. After the

hearing thresholds were fed into the software (NOAH-3.0 and Connex 5), the digital hearing aids

were programmed based on the NAL-NL1 prescriptive procedure. An acclimatization level of 2

was used while programming and the volume control was disabled for the digital hearing aids.

Phase 2: Insertion gain measurements

The following steps were used to select the hearing aid for each participant before the

measurement of the aided benefit.

Otoscopic examination was done before the commencement of the testing to rule out any

contraindication for insertion gain measurement.

The participant was seated in front of the loudspeaker of the hearing aid test system for

the measurement of the insertion gain. For this purpose the loud speaker of the test

system was located on the speaker stand at 45 degrees Azimuth and at a distance of one

foot from the participant‟s test ear.

The reference and the probe tube microphones were placed near the test ear and the

instrument was leveled.

The audiometric thresholds of the participant were fed into the hearing aid test system

and the target gain curve was derived based on NAL-2 fitting formula.

The stimulus was routed through the loudspeaker. The stimulus was American National

Standards Institute (ANSI) digi-speech at 50, 65 and 90 dB SPL. The sound pressure

level in the ear canal of the test ear was measured by means of a pre-measured length of

the probe tube microphone inserted in the test ear. The reference microphone was located

on the band above the test ear. The reference microphone also measured the signal level

at different frequencies. The difference between the levels measured by the probe tube

microphone and the reference microphone was displayed on the monitor of the hearing

aid test system. Thus the Real Ear Unaided Response (REUR) was measured and stored.

Then the programmed digital hearing aid was switched „on‟ and fitted to the test ear of

the participant. Care was taken to see to it that the length of the probe tube in the ear

canal was not changed. The Real Ear Aided Response (REAR) was measured for the

same stimulus i.e., ANSI digi-speech at 50, 65 and 90 dB SPL.

After the measurement of the REUR and REAR, the Real Ear Insertion Gain (REIG =

REAG – REUR) at different frequencies was computed by the instrument. The REIG at

different frequencies was displayed as Real Ear Insertion Response curve (REIR). Thus,

the REIR was obtained for the hearing aid for both the ears of each participant.

This was repeated for three hearing aids in order to select the best hearing aid based on

the REIR that matched the target gain curve for testing the performance.

Phase 3: Establishing of Speech Recognition Scores (SRS)

The participants were seated comfortably in the sound treated audiological test room with the

appropriate loud speakers located at one meter from the participant at 45 degrees Azimuth. The


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Speech Recognition Scores (SRS) for Kannada Phonemically Balanced word list (Yathiraj &

Vijayalakshmi, 2006) for each participant was noted down in the following four conditions.

1. Unaided condition

2. Aided conditions -

2. A. with binaural analog hearing aids (AA)

2. B. with binaural digital hearing aids (DD)

2. C. with digital hearing aid in one ear and analog hearing aid in the opposite ear (AD).

In the unaided condition the SRS was obtained. For this one of the four Phonemically

Balanced word lists (Yathiraj & Vijayalakshmi, 2006) was presented using monitored live voice,

at 45 dBHL, in sound field condition where the stimulus was routed through the speaker. The

participant was instructed to repeat the words presented. The number of words repeated correctly

was scored. Each correct repetition was given the score of one, the maximum score being 25, as

the list consisted of 25 words.

Then one of the combinations of the hearing aids (2A, 2B or 2C) was fitted in the

participant‟s ear. If it was the condition 2C, then analog hearing aid was fitted in one ear and the

digital hearing aid in the other ear. Order of testing the aided condition was randomized across

the participants to overcome the effect of order of the conditions i.e., the conditions in which the

participants were tested were randomized between participants in order to avoid the order effect.

Thus at the end of the third phase SRS in the four test conditions (unaided and three aided

conditions) were obtained for each participant.

Phase 4: Quality rating of speech through the hearing aids

In each test condition (AA, DD & AD), after the SRS was obtained the participant

listened carefully to a CD recorded sample of a passage in Kannada, played through a CD player

connected to the audiometer. Each participant was instructed to listen to the recorded passage

and to rate the quality of the recorded passage. The rating was based on three parameters of aided

speech such as loudness, clarity and intelligibility. Loudness was defined as the perception of

psychological impression of intensity of sound (Stach, 1997). Clarity was defined as the

distinctness (or) purity of tone (Cecil & Patridge, 1970). Intelligibility was defined as the correct

understanding ability of the speech units. A ten point rating scale was used for rating each of

these parameters. The scale for the three parameters of aided speech was as follows:

For loudness: 1 - Very soft (can‟t hear)………………….10 - uncomfortable

For clarity: 1 - Completely unclear…………………….10 - very clear

For intelligibility: 1 - Completely unintelligible……………...10 - fully intelligible

The participant was instructed to listen to the recorded passage presented at 45 dBHL

through loud speaker of the audiometer. Using the above rating scale the participant was

requested to listen to and rate the recorded passage in each of the three aided conditions. The


27

quality rating of connected discourse was also analyzed in order to find out the difference in

speech perception when using any of the three conditions.

Phase 5: Measurement of signal processing delay

The group delay is the amount of time it takes the digital hearing aid to process sound.

The processing delay for some hearing aids is so slight that it is imperceptible to the human ear.

The processing delay for other aids can extend to several milliseconds- longer than the

calculating time for an analog hearing aid. If an individual is fit monaurally with an aid with a

significant digital processing delay that person might experience some confusion because his

unaided ear will be hearing sounds slightly faster than his aided ear. The processing delay of the

hearing aids used was measured for the purpose of comparing the performance of the hearing

aids in the three aided conditions. The following steps were used for measuring the processing

delay of the hearing aids used.

The enhanced DSP screen was selected from the opening screen of the hearing aid test system.

The sound chamber was leveled and the hearing aid was placed for testing in the sound chamber.

That is, the hearing aid was connected to a 2 cc coupler and the output was collected through a

test microphone for analysis.

The hearing aid with the coupler and the microphone were placed in the anechoic chamber and

the measurement for the processing was performed.

The processing delay measurement was taken by sending a short impulse from the sound chamber

speaker to the hearing aid.

For the processing delay measurements the hearing aid test system microphone collected

information from the hearing aid for 20 msec. from the time the impulse was delivered which was

a series of varying amplitudes.

The data collected in the digital processing delay measurement were displayed in the graphical

format as amplitude vs. time (Figures 1&2). The delay point is represented by a dotted vertical

line along with the display of numerical data. There was a second dotted vertical line showing the

delay for reference.

Fig. 1. Measurement of the processing or group delay of a digital hearing aid


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Fig. 2. Measurement of the processing or group delay of an analog hearing aid

The data collected from this measurement was displayed in a graphical format 20 msec. wide. The

measurement from the vertical point to the response wave of the hearing aid is taken as the processing

delay of that hearing aid.

Similarly the processing delay of all the test hearing aids used was measured and the values were

compared according to different aided conditions for the testing.

Thus the SRS and ratings for quality of speech (loudness, clarity and intelligibility) were

made for the three aided conditions and the data on processing delay were collected. The results

were analyzed to evaluate the objective of the study.

Results and Discussions

The objective of the study was to compare the performance of 15 participants with

bilateral symmetrical sensorineural hearing loss, in terms of audibility, recognition and quality of

speech using the three aided conditions, viz., binaural analog hearing aids, binaural digital

hearing aids and binaural amplification with analog and digital hearing aids in opposite ears.

The objective of the present study was evaluated by obtaining the Speech Recognition

Scores (SRS) and the quality rating of speech. The quality of speech was rated on three

parameters such as loudness, clarity and intelligibility in the three aided conditions; AA, DD and

AD. The data were tabulated and statistically analyzed using the Statistical Package for Social

Sciences (SPSS, version 10.0).

The mean and standard deviations of the following measures were computed for all the

three aided conditions. Following this, pair-wise comparisons were made to see if there was a

significant difference between the aided conditions. The results are given below under three main

headings.

I) Speech Recognition Scores (SRS)

II) Quality rating of speech

III) Hearing aid processing delay.


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I. Speech Recognition Scores (SRS)

The SRS in the three aided conditions were analyzed. Table 1 depicts the mean and

standard deviation (SD) values of the SRS obtained in the three aided conditions. The three aided

conditions include analog binaural hearing aids (AA), digital binaural hearing aids (DD) and

analog hearing aid in one ear and digital hearing aid in the other ear (AD). As can be observed in

the Table 1 the mean SRS value was more in the DD condition and least in the AA condition.

The variation of SRS, i.e., SD in different conditions was comparable.

Table 1: Mean and Standard Deviation values of SRS obtained in the three aided conditions

Mean SD

SRS – AA 19. 60 4. 03

SRS – DD 22. 13 3. 54

SRS – AD 21. 33 3. 59

Note: SRS-AA: SRS with binaural analog hearing aids; SRS-DD: SRS with binaural digital hearing aids; SRS-AD:

SRS with analog hearing aid in one ear and digital hearing aid in the opposite ear.

Further, one way repeated measures Analysis of Variance (ANOVA) was performed to

see if the difference in the mean SRS values in the three aided conditions were significantly

different. The results showed that there was a significant difference between the three conditions,

F =(2, 28) = 9.73, (p < 0.01), indicating that there was a significant effect of the aided conditions.

Further the mean values of SRS in AD condition was higher than the mean value of SRS in AA

condition and the mean SRS values in DD condition was higher than that in the AD condition.

From Bonferroni‟s multiple comparison it was observed that there was no significant difference

between the AA and AD conditions and the AD and DD conditions (p > 0.05). However, there

was a significant difference between AA and DD conditions (p < 0.05).

This result is consistent with that reported by Prinz, Nubel and Gross (2002) who had got

similar results while testing on individuals with bilateral moderately-severe symmetrical hearing

loss. Interestingly all the studies that had proved the advantage of binaural amplification had

used ear level hearing aids, such as those by Jerger and Dirks (1961), MacKeith and Coles

(1971) and the others.

II. Quality rating of speech

Quality rating of hearing aid processed speech was done on three sub-scales. They were

loudness, clarity and intelligibility. The three sub-scales were rated on a ten- point rating scale,

one being very soft and ten being uncomfortable for loudness, one being completely unclear and

ten being very clear for clarity and one being unintelligible and ten being fully intelligible for

intelligibility.

From the Table 2, it can be observed that the mean values for quality ratings of loudness,

quality and intelligibility is higher for the DD and the AD conditions compared to the AA

condition but in all the quality ratings, the value of DD condition is higher than the AD


30

condition. The variation as revealed by the SD was slightly higher in the AA condition than in

the AD condition, which in turn was higher than in the DD condition.

Table 2: Mean and SD of ratings on loudness, clarity and intelligibility in AA, DD and AD

conditions

Quality sub-scales Aided conditions Mean (N=15) SD

Loudness

AA 6.93 2.46

DD 7.93 1.98

AD 7.66 2.05

Clarity

AA 6.40 2.13

DD 8.20 1.42

AD 8.00 2.00

Intelligibility

AA 7.06 2.15

DD 8.46 1.30

AD 7.86 1.95

II. a. Loudness

Friedman‟s test, a non-parametric equivalent of one way repeated measures ANOVA,

was used for comparison of ratings for loudness between the three aided conditions. From

Friedman‟s test no significant difference was found between the loudness ratings of the three

aided conditions [X^2(2) = 5.568, p > 0.05].

II. b. Clarity

Friedman‟s test was used for comparison of ratings for clarity in the three aided

conditions and the results showed a significant difference between the aided conditions AA, DD

and AD [X^2 (2) = 13.792, (p < 0.01)]. Wilcoxon‟s signed rank test (a non-parametric equivalent

of paired t-test), was used for pair-wise comparison of the three aided conditions which revealed

no significant difference between the AD and DD conditions (p > 0.05). However, a significant

difference between AA and AD conditions (p < 0.01) and the AA and DD conditions (p < 0.01)

were noted.

II. c. Intelligibility

Friedman‟s test was used for the comparison of intelligibility ratings for the three aided

conditions which showed significant difference between the aided conditions [X^2 = 6.545, (p <

0.05)]. Wilcoxon‟s signed rank test was performed for the pairwise comparison of the three aided

conditions which revealed no significant difference between the AD and AA (p > 0.05) and AD

and DD (p > 0.05) conditions. However, a significant difference between the DD and AA (p <

0.05) conditions was noted.

III. Hearing aid processing delay

Frye (2001) reported that one of the properties of the digital technology is that it always

takes time to process digital data. Group delay is the delay between input and output of the

digital hearing aid (Kates, 2003). The processing delay for some hearing aids is so less that it is


31

imperceptible to the human ear. The processing delay for other hearing aids can extend to several

milliseconds. For analog hearing aids, the processing delay would be comparatively very less

because it does not perform any signal processing activities like the digital hearing aid. Kates

(2003) suggested that even before the delay in the digital processing is considered the other

components of the hearing aid (microphone, receiver, A/D or D/A) and the acoustic interactions

will contribute from 2 to almost 5 msec. group delay. This depends on the sampling rate and the

algorithm/s implemented. The processing delay of the hearing aids used in the present study is

tabulated below.

Table 3: Processing delay of the hearings aids used

Hearing aid Processing delay

(msec)

Analog 1 0.4

Analog 2 0.4

Digital 1 0.9

Digital 2 0.9

From the Table it can be seen that the processing delays of the two analog hearing aids

were the same and that of the two digital hearing aids were also the same. As suggested by Stone

and Moore (2003) a processing delay of 32 msec. could be allowed for an effective speech

perception for individuals having hearing impairment of about 55 dBHL. The finding of the

study done by Henrickson (2004) also supported that of Stone and Moore concluding that

processing delays of about 0.3 to 0.7 msec. are acceptable for analog hearing aids and about 1 to

11 msec. are acceptable for digital hearing aids. Dillon (2001) by comparing five digital hearing

aids on individuals with hearing impairment concluded that a processing delay of 1.2 to10 msec.

were acceptable and there was no correlation between hearing aid preference and the processing

delay. Flame (2002) concluded that if mismatch in delay times did not change often individuals

with hearing impairment adapt with a period of hours or days. Though presently there is a

difference in the group delay between the analog (i.e., 0.4 msec.) and the digital (0.9 msec)

hearing aids, with evidence from the literature, in the present study also it is inferred that the

individuals with hearing impairment will adapt to the processing delays between analog and the

digital hearing aids. However, audiologist should keep in mind that the group delays between the

two hearing aids should not vary much for providing effective speech perception.

From the findings of the present study it can be inferred that the clients could be

recommended with one analog and one digital hearing aid in the opposite ears till they could

afford another digital hearing aid. However, the processing delay of the hearing aids needs to be

measured for optimum performance in such situations. This is due to the advantages of binaural

amplification and keeping in mind the better performance of binaural digital hearing aids

compared to analog, in terms of clarity, intelligibility and loudness.


32

References

Condie, R., Scollie, S. & Checkly, S. (1984). Children‟s performance with analog vs. digital

adaptive dual microphone hearing aid. Ear & Hearing, 19(5), 407-413.

Frye, G. J. (2001). Testing digital and Analog Hearing Instruments: Processing Time Delays and

Phase Measurements. A look at the potential side effects and ways of measuring them.

http://www.frye.com/library/acrobat/hrarticle2.pdf.

Jerger, J. & Dirks, D. (1961). Binaural hearing aids: An enigma. Journal of the Acoustical

Society of America, 19, 629-631.

Mc. Keith, N.W. & Coles, R.A. (1971). Binaural advantages of hearing in speech. Journal of

Laryngology and Otology, 85, 231-232.

Markides, A. (1977). Binaural amplification. NY: Academic Press.

Yathiraj, A. & Vijayalakshmi, C. S. (2006). Phonemically balanced word list in Kannada

developed at the dept. of Audiology, AIISH.

Kates, J. M. (2003). Dynamic range compression using digital frequency wrapping. US patent

application 20030081804, tia.sagepub.com/cgi/content/ref/8/3/84.

Hirsh, I. J. (1995). Pre-attentive discriminability of sound order as a function of tone duration

and interstimulus interval: A mismatch negativity study. Audiology and Neurotology,

4(6), 303-310.

Nabelek, A. K. & Robinson, P. K. (1982). Monaural and binaural speech perception in

reverberation for listeners of various ages. Journal of Acoustical Society of America, 71,

1242-1248.

Prinz, I., Nubel, K. & Gross, M. (2002). Digital and analog hearing aids in children. Is there a

method for making an objective comparison possible? http://www/medical/mm_

0093_coveragepositioncriteria_hearingaids.pdf

Ross, M. (1997). A retrospective look at the future of aural rehabilitation. Journal of American

Academy of Audiology, 30, 11-28.

Sanders, D.A. (1977). Auditory perception of speech. NJ: Prentice Hall, Inc.

Sanders, D.A. (1982). Aural rehabilitation; A management model. 2nd

edn. NJ: Prentice Hall, Inc.

Sanders, D.A. (1993). Management of hearing handicap: Infants to elderly. NJ: Prentice Hall,

Inc.

Stone, M.A. & Moore, B.C.J. (2003). Tolerable hearing aid delays: effect on speech production

and perception of across frequency variation of delays. Ear & Hearing, 24(2), 175-183.

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http://www/medical/mm_%200093_coveragepositioncriteria_hearingaids.pdf




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Reduction of Stimulus Artifacts in ASSR: An Investigation of a

Stimulus Approach

Arivudai Nambi P & C S Vanaja

Abstract

Auditory steady state responses at high stimulus levels were contaminated by artifacts

when weighted averaging method as well as phase coherence method is used detect responses.

The current study aimed to determine the upper limit for artifact free ASSR for stimuli presented

through headphone and bone vibrator. The current study also investigated whether artifacts can

be avoided by changing the carrier frequency in such a way that they are not integer multiple of

sampling frequency. ASSR was recorded in 30 individuals with profound hearing loss who did

not show behavioural responses even at the upper limit of ASSR system. The results revealed that

the upper limit for artifact free ASSR measurement for head phone is 90 dB HL and for bone

vibrator is 50 dB HL. Changing the carrier frequency enhanced the dynamic range for artifact

free ASSR measurement obtained through headphone and bone vibrator.

Introduction

Auditory steady state response (ASSR) is one of the objective methods for estimation of

behavioural thresholds (Cone-wesson et al., 2002; Aoyagi et al., 1994; Luts & Wouter, 2005).

ASSR examines the response for sinusoids that are amplitude, frequency or mixed modulated

stimuli. Since stimuli used for ASSR recording is continuous and modulated in nature it is

possible to present a stimuli upto 120 dB HL also. This feature allows the ASSR to assess the

hearing threshold levels greater than 80 dB HL and it differentiates severe to profound hearing

loss (Rance et al., 1998; Rance et al., 1993; Swanepoel, Hugo & Roode, 2004). Gorga et al.

(2004) initially pointed out the presence of artifactual ASSR at higher levels (>95 dBHL) in

individuals with profound hearing loss who did not show any behavioral responses to modulated

stimuli even at the upper limits of ASSR system. The presence of these artifacts was also

supported by other investigators (Small & Stapells, 2004; Picton & John, 2004). Presence of

these artifacts at higher level might limit the ASSR‟s application to differentiate between severe

and profound hearing loss. Picton and John (2004) have reasoned out that “aliasing” error cause

the occurrence of artifacts at higher levels. Aliasing occurs when signal is sampled at a rate

lower than twice its frequency. Then the signal is seen at a frequency equal to absolute frequency

and its closest multiple integer of sampling rate. The sampling rate used in the ASSRs is




34

designed for the efficient analysis of the responses at the frequencies of modulation. Small and

Stapells (2004) explained that frequency of the aliasing error which occur in ASSR can be

predicted by the formula,

Alias frequency = Closest integer multiple of sampling frequency- Input frequency

For example a 500 Hz tone that is amplitude modulated at 80 Hz would have energy at

420, 500, 580 Hz. If this energy is present in the EEG being digitized at 500 Hz an alias

frequency would be 500Hz-420Hz = 80Hz which is exactly the same as the modulation rate for

this 500 carrier frequency. This was explained with respect to weighted averaging method of

response detection (spectrum of the responses was considered) which makes use of F-test.

Artifacts were also present in instrument which uses phase coherence to detect responses and the

upper limit for artifact free ASSR measurement for head phone is 95 dBHL and for insert ear

phone is 105 dBHL (Narne, Nambi & Vanaja, 2006). Picton and John (2004) used different

approaches to eliminate artifacts by shifting the aliasing frequency away from the modulation

frequency. These approaches include the use of different stimuli such as „beats‟ which has the

energy at carrier frequency half of modulation frequency, sinusoidally alternated amplitude

modulated tone which has the energy at carrier frequency 3/2 times of modulation frequency

and carrier frequency half of modulation frequency and changing the A/D conversion rates.

These approaches have shown to be effective in avoiding artifacts when ASSR is recorded using

weighted averaging method. It is not known whether these techniques will help in reducing

artifacts in ASSR recorded using phase coherence method. Another approach which can

probably shift the aliasing frequency away from the modulation frequency is using a carrier

frequency which is not an integer multiple of sampling frequency (Picton & John, 2004).

Research needs to be done to check whether changing the carrier frequency can avoid the

artifacts or enhance the dynamic range of ASSR for artifact free measurements. So, the current

study was aimed to investigate whether changing the carrier frequency can avoid artifacts while

recording ASSR using phase coherence method. The study also aimed at determining the upper

limit for artifact free ASSR measurements for stimuli presented through a bone vibrator.

Method

Participants

Thirty individuals with profound hearing loss ranging in age from 18 to 40 years

participated in the current study. ASSR was recorded from 15 participants for stimuli presented

through head phone and from 15 participants for stimuli presented through a bone vibrator. It

was ensured that the subjects did not show any behavioral responses to mixed modulated stimuli

used for recording ASSR at the presentation level used in the experiment.

Instrumentation

A calibrated two channel diagnostic audiometer Madsen OB 922 audiometer with TDH

39 headphone and Radio ear B71 bone vibrator was used to estimate the behavioral thresholds.


35

GSI- Audera version (1.0.2.2) was used to record ASSR as well as to obtain behavioral

thresholds to mixed modulated stimuli presented through headphone and bone vibrator.

Procedure

Pure tone audiometric thresholds and behavioral thresholds to the modulated tones were

measured using modified Hughson & Westlake (Carhart & Jerger, 1959) procedure. Behavioral

thresholds to modulated stimuli were obtained at 500, 1000, 2000 and 4000 Hz, hereafter

referred to as conventional carrier frequencies, and 522, 1022, 2022, & 4022 Hz, hereafter

referred to as experimental carrier frequencies, in the current study. These measurements were

carried out to ensure that the participants meet the subject selection criteria.

For recording ASSR, subjects were seated comfortably in a reclining chair and they were

asked to relax or sleep. Electrode sites were cleaned using skin prepping gel. Silver chloride

electrodes were used to record the ASSR using three electrode placement. For air conduction

measurement, inverting electrode was placed on the test ear mastoid, non inverting electrode was

placed on the fore head and ground electrode was placed on the mastoid of non test ear. For bone

conduction measurements non inverting electrode was placed at vertex and the site for inverting

and non inverting electrodes were same as that used for air conduction measurements. It was

ensured that electrode impedances were less than 5 k Ohms and inter electrode impedance was

less than 2 k Ohms.

For air conduction measurements supra aural headset was placed over the pinna and for

bone conduction measurements a bone vibrator was placed on the fore head. ASSRs were

recorded for both conventional carrier frequencies, 500, 1000, 2000 and 4000 Hz as well as for

experimental carrier frequencies 522, 1022, 2022 and 4022 Hz in all the subjects. ASSR

measurements were performed using high modulation frequency of 74 Hz for 500 & 522 Hz , 81

Hz for 1000 & 1022 Hz, 88 Hz for 2000 and 2022 Hz, and 95 Hz for 4000 & 4022 Hz carrier

frequencies. Testing was initiated at the maximum limits of instrument and the intensity was

varied in 5 dB steps to find out the highest intensity level at which artifact free ASSR

measurements can be obtained. Response was determined automatically by the instrument using

phase coherence method.

Results

It was observed that less number of individuals had artifacts for experimental carrier

frequency when compared to conventional carrier frequencies. Figure 1 and 2 depicts the number

individuals with artifacts for conventional and experimental carrier frequencies for air conducted

and bone conducted stimuli. From the figures it is clear that as the carrier frequency increases the

number of individuals with artifacts reduces for both conventional and experimental carrier

frequencies obtained through headphone and a bone vibrator.


36

0

2

4

6

8

10

12

14

No

of s

ubje

cts

500 1000 2000 4000

Frequency

Conventional CF

Experimental CF

Figure 1: Number of individuals with artifacts for air conducted stimuli

0

2

4

6

8

10

12

No

of

su

bje

cts

500 1000 2000 4000

Frequency

Conventional CF

Experimental CF

Figure 2: Number of individuals with artifacts for bone conducted stimuli

Overall percentage of subjects in whom artifacts were observed is more for air

conduction transducer when compared to bone conduction transducer. Table 1 depicts the

percentages of subjects in whom artifacts were observed for conventional and experimental

carrier frequencies recorded using air conduction and bone conduction transducer.

Table 1: Percentage of subjects with artifacts for conventional & experimental carrier frequencies

Frequency

Percentage (%)

Head phone Bone vibrator

500 93.3 91.6

1000 80.0 46.15

2000 66.6 40.0

4000 26.6 26.6

522 66.6 33.3

1022 40.0 23.07

2022 13.5 0.0

4022 0.0 0.0

It was observed that the minimum level at which artifacts occurred was higher for

experimental carrier frequencies when compare to conventional carrier frequencies. Table 2

shows the mean and standard deviation of minimum levels at which artifacts occurred across the


37

carrier frequencies for air conducted and bone conducted stimuli and maximum intensity at

which artifact free ASSR can be recorded.

Table 2: Mean and SD of minimum level at which artifact occurred and the maximum limit for

artifact free ASSR measurement in dBHL

Frequency

Transducer

Head phone Bone vibrator

Lowest level at

which artifacts

occurred

Mean (SD)

Max limit for

obtaining

artifact free

ASSR

Lowest level at

which artifacts

occurred

Mean (SD

Max limit for

obtaining artifact

free ASSR Max

limit

500 Hz 98.57

(4.97)

85 56.81

3.37

45

522 Hz 106.0

(3.94)

95 60.0

0.00

55

1000 Hz 109.16

(6.33)

90 73.33

2.58

65

1022 Hz 112.5

(3.94)

100 78.33

5.00

70

2000 Hz 108.0

(5.37)

95 80.83

6.40

65

2022 Hz 110

(0.00)

105 >80 80

4000 Hz 112.5

(5.00)

100 70.00

0.00

65

4022 Hz >115 115 >70 70

Discussion

In the present study it was found that using the experimental carrier frequency reduces

the presence of artifacts. The exact sampling frequency that is used in instrument is not known.

However Small and Stapells (2004) reported that commercially available ASSR systems use the

A/D to conversion rates of 500 Hz or 1000 Hz as default setting. So it was assumed that this

instrument also uses similar A/D rate and the carrier frequencies were changed in such a way that

they were not integer multiple of 500 Hz or 1000 Hz. Results revealed that using the

experimental carrier frequency reduced the occurrence of artifacts. This supports the notion that

these artifacts might be due to electro magnetic aliasing effect. The change in carrier frequency

may not allow the electromagnetic carrier signal to alias at the modulation frequency if the A/D

rates are 500 Hz or 1000 Hz (Picton & John, 2004). Similar results have been reported by other

investigators when they changed the sampling rate (Picton & John 2004; Small & Stapells 2004)

The artifact reduction for stimuli of low frequencies (522 & 1022 Hz) is less when

compared to high frequencies (2022 & 4022 Hz). The persistence of artifacts at low frequencies


38

may be attributed to physiological artifacts. The artifacts may be of vestibular origin. Vestibular

stimulation is larger at low frequencies when compared to high frequencies (Townsend & Cody,

1971; Todd, Cody & Banks, 2000). Small and Stapells (2004) reported that vestibular evoked

myogenic potential from inion muscle could be recorded by an electrode placed on the nape.

However in the present study electrodes were placed on mastoids and forehead/vertex. This

electrode placement is not suited for picking vestibular evoked myogenic potentials. There are

reports of a negative potential N3 generated from the vestibular nuclei through stimulation of

saccule (Nong, Ura & Noda, 2000) which could be picked up by using conventional electrode

placements (Fore head/Vertex to mastoid) in profound hearing loss individuals. An investigation

by Narne, Nambi and Vanaja, (2006) also supported the possibility of vestibular artifacts while

recording ASSR at high intensity based on latency calculations from the phase delay which falls

around 3-5 msec. They reported that these physiological artifacts mainly contaminated the ASSR

elicited by 500 Hz carrier signal. However in the current study the artifacts persisted for 1022 Hz

carrier signal also. Occurrence of artifacts at this frequency may also be of vestibular origin.

Vestibular stimulation by 1000 Hz acoustic signal has also been reported in the literature (Cheng,

Huang & Young, 2003; Welgampola & Colebatch, 2001). Another possible reason for obtaining

more artifacts at low frequencies are related to the electrical energy required to drive the

oscillator. It has been reported that less electrical energy is required to drive the oscillator at high

frequencies (2000 Hz & 4000 Hz) when compared to low frequencies (Small & Stapells, 2004).

So the electromagnetic energy that radiated during the generation of high frequency signals will

be less when compared to low frequency signals which in turn might reduce the amplitude of

electromagnetic stimulus artifacts. A third reason may be that the higher carrier frequencies will

be away from the EEG low pass filter setting and thus stimulus artifact would be smaller in

amplitude (Small & Stapells, 2004).

Results revealed that there were fewer artifacts for bone conducted stimuli when

compared to air conducted stimuli. In the current study the bone vibrator was placed on the

forehead and the electrodes were placed on mastoids and vertex. For air conduction testing the

electrodes was placed on the mastoids and forehead. So the physical proximity between the

transducer and the electrode was more in case of bone vibrator when compared to headphone.

This might have reduced the amplitude of electromagnetic energy reaching the electrode which

in turn probably reduced the occurrence of artifacts. Also forehead placement of the bone

oscillator might result in less vestibular stimulation, possibly due to the different mode of

stimulation compared with temporal bone placement (Small & Stapells, 2004). In the current

study ASSR for air conducted and bone conducted stimuli was not obtained from the same

subject due to time constraints. The individual variability among the subjects may also have

accounted for the difference in the percentage of subjects in whom artifacts were observed.

The upper limits for artifact free ASSRs elicited by experimental carrier frequencies were

high when compared to ASSRs elicited by conventional carrier frequencies. This may be because

experimental carrier frequencies reduced the electromagnetic artifacts and were mainly

contaminated by physiological artifacts. The physiological artifacts might occur at little higher


39

intensities when compared to stimulus artifacts and this probably enhanced the upper limits for

artifact free ASSR measurements for experimental carrier frequencies.

It can be concluded from the present study that percentage of subjects in whom artifacts

were observed for conventional carrier frequencies are higher when compared to experimental

carrier frequencies. The important clinical implication of the current study is that the

experimental carrier frequencies can be used for threshold estimation as the dynamic range for

artifact free ASSR measurement is higher for experimental carrier frequencies when compared to

conventional carrier frequencies.

References

Aoyagi, M., Kiren, T., Furuse, H, Fuse, T., Suzuki, Y. & Yokota, M. (1994). Pure-tone threshold

prediction by 80 Hz amplitude-modulation following response. Acta Otolaryngology,

Supplement, 511, 7–14.

Carhart, R. & Jerger, J. (1959). Preferred method for clinical determination of pure-tone

thresholds. Journal of Speech and Hearing Research, 24, 330–45.

Cheng, P.W., Huang, T.W. & Young, Y.H. (2003). The influence of clicks versus short tone

bursts on the vestibular evoked myogenic potential. Ear and Hearing, 24, 195-197.

Cone-Wesson, B., Rickards, F., Poulis, C., Parker, J., Tan, L. & Pollard, J. (2002). The auditory

steady-state response: clinical observations and applications in infants and children.

Journal of the American Academy of Audiology, 13, 270-282.

Gorga, M.P., Neely, S.T., Hoover, B. M. Dierking, D.M., Beauchiane, K.L. & Manning.C

(2004). Determining the upper limits of stimulation for auditory steady state response

measurements, Ear & Hearing, 25, 302 – 307.

Luts, H. & Wouters (2005). Comparision of MASTER and AUDERA for measurement of

auditory steady state responses. International Journal of Audiology, 44, 244-253.

Narne, V. K., Nambi, P. A. & Vanaja, C.S. (2006). Artifactual responses in auditory steady state

responses. Paper presented at 38th

Annual Conference of the Indian Speech and Hearing

Association, Ahmedabad, India.

Nong, D.X., Ura, M. & Noda, Y. (2000). An acoustically-evoked short latency negative response

in profound subjects. Acta Otolaryngologica, 128, 960-966.

Picton, T,W. & John,M. (2004). Avoiding electromagnetic artifacts when recording auditory

steady state responses. International journal of audiology, 15, 541-554

Rance, G, Dowell, R.C., Rickards, F.W., Beer, D.E. & Clark, G.M. (1998). Steady state evoked

potential and behavioral hearing thresholds in a group of children with absent click

evoked auditory brainstem response. Ear & Hearing, 19, 48-61.

Rance, G., Rickards, F.W., Cohen, L.T., Burton, M.J. & Clark, G.M. (1993). Steady state evoked

potentials. Advancements in Otorhinolaryngology, 48, 44-48.

Small, S. A. & Stapells, D. R. (2004). Artifacutal responses when Auditory Steady State

Responses, Ear and Hearing, 25, 611-623.


40

Swanepoel, D., Schmulian, D. & Hugo, R. (2004). Establishing normal hearing with the dichotic

multiple frequency auditory steady state response compared to an ABR protocol. Acta

Otolaryngology, 124, 62-67.

Todd, N., Cody, P. & Banks, P. (2000). A saccular origin of frequency tuning in myogenic

vestibular evoked potentials. Hearing Research, 141, 180-188.

Townsend, G. L. & Cody, D. (1971). The averaged inion response evoked by acoustic

stimulation: its relation to the saccule. Annals of Otology, 80, 121-132.

Welgampola, M.S. & Colebatch, J.G. (2001). Characteristics of tone burst-evoked myogenic

potentials in the sternocleidomastoid muscles. Otology and Neurotology, 22, 796-802.


41

Comparison of Word Recognition Scores using Different Settings of

Telecoil in a Digital Hearing Aid

Bijan Saikia & P Manjula

Abstract

This article describes the performance of individuals with hearing impairment while

using telephone as a means of communication. Listeners with hearing impairment almost always

perform poorly while using telephone as compared to face-to-face conversation. The present

study intended to evaluate the optimal settings by comparing the default and modified telecoil

settings needed for best performance over telephone.15 participants with moderate to

moderately-severe sensorineural hearing loss participated in the study. The word recognition

scores, using Phonemically Balanced Kannada word lists, were compared in different telecoil

settings of the hearing aid. The results revealed a significant difference between the scores

obtained with the different settings of the hearing aid, that is, default and modified telecoil

settings of the hearing aid. Modifications of the default telecoil setting are required to optimize

performance.

Key words: telecoil settings, teleboard, telewand.

Introduction

Hearing aid users have often expressed their dissatisfaction while using telephone

(Kochkin, 2002). Listeners with hearing impairment almost always perform poorly while using

telephone as compared to face-to-face conversation. Although audiologists carefully adjust the

electro acoustic characteristics of a hearing aid in the microphone mode in an attempt to improve

speech understanding, very little attention has been given to the output characteristics of telecoil

and how well individuals with hearing loss understand speech over the telephone when using

telecoil mode (Takahashi, 2005). A hearing aid telecoil enables a hearing aid user to listen over

the telephone without any acoustic feedback by taking advantage of the electro magnetic

induction (Skinner, 1988). This phenomenon is known as inductive coupling and was first

reported in 1947 by Sam Lybarger. Inductive coupling refers to the phenomenon whereby an

electrical current is induced in a coil of wire as a time varying magnetic field passes through the

coil (Ross, 2005). Advantages of using induction coil input mode rather than microphone mode

include reduced acoustic feedback problems and elimination of ambient noise surrounding the

hearing aid wearer while using a telephone.

The telecoil of the hearing aid is not as sensitive as the microphone input. In addition the

telephone system itself presents limitation on the signal received, the most notable being the

Professor of Audiology, All India Institute of Speech and Hearing, Mysore, India



42

band-limiting nature of telephone transmissions. The transmitting bandwidth of the telephone is

approximately 3000 Hz, transmitting frequencies between 300 and 3300 Hz, with a relatively flat

spectrum. Although listening via inductive pick-up is often effective, problems can occur if

interfering magnetic sources such as digital cellular phones, power lines, transformers,

fluorescent lights and computer peripherals are nearby (Levitt, 2001). Another issue that comes

into consideration while using hearing aid with telephone is the hearing aid compatibility (Smith,

1971) The 1988 law states that a telephone is hearing aid compatible (HAC) if it “provides

internal means for effective use with hearing aids that are designed to be compatible with

telephones which meet established technical standards for hearing aid compatibility” established

by Electronic Industries Association (EIA) Standard RS-504.

A major factor influencing responses through inductive coupling is the physical

orientation of the T-coil relative to the electromagnetic field. Compton (1994) discussed the

relationship between telecoil sensitivity and its orientation and Revit (1996) from the perspective

of an audiologist and a hearing aid wearer, cited positioning and orientation as an essential part

of instructions to new telecoil users.

Many newer hearing aids now allow programmable adjustments of the level and

frequency response of the telecoil. Some manufacturers offer a telecoil that enables the hearing

aid user to access the telecoil without even having to manually switch to the telecoil mode, that

is, the “touchless” telecoil. It is often problematic to set the telecoil response as there are many

factors that influence real world speech communication over the telephone, such as, the

characteristics of the listener‟s as well as the talker‟s telephone, variability in transmission line

characteristics, variability in the position of the telephone handset relative to the telecoil and

interference from other electromagnetic sources (Takahashi, 2005).

Despite these challenges, in clinical situation, it may be valuable to program a hearing

aid‟s telecoil response based on the performance. Programming the telecoil seems to require the

same target that is used for acoustic response which may not be appropriate for telephone use

because of factors such as the frequencies transmitted through a telephone line and electro-

magnetic field strength around the telephone (Davidson & Noe, 1994). The target is for acoustic

input through microphone mode. Input through telecoil differs and hence target should be

different. Hence, the performance in telecoil mode is lesser than for microphone mode.

At present, provisions are there in the hearing aid analyzer system for measurement with

„teleboard‟ as well as „telewand‟ to evaluate the electroacoustic performance of the hearing aid in

the „T‟ mode and it is also important to know how the electroacoustic characteristics for telecoil

vary depending on the type of input source that is, „teleboard‟ or „telewand‟.

Although there is a capability to program the overall gain and frequency response of the

telecoil in some hearing aids, there is no standardized method of setting these parameters. Yanz

and Preves (2003) reported that inductive coupling is better in the high frequencies than in the

low frequencies. For this reason the low frequency response of the hearing aid is often boosted

relative to the high frequency response to compensate for poor coupling in the low frequency


43

(Compton, 1994). In 2007, Chowdhury, Manjula and Abraham have also reported of findings

similar to that of Yanz and Preves (2003). That is, they reported inductive coupling to be greater

in the high frequencies than in the low frequencies. Takahashi (2005) studied the effect of

different telecoil settings on the word recognition scores. The two settings used were default

setting obtained by simply switching to the telecoil mode without making any modifications and

the modified telecoil settings obtained by changing the telecoil settings in an attempt to match

the acoustic frequency response target.

The present study aimed at -

Evaluating the optimal settings of the telecoil by comparing the performance in

terms of default and modified telecoil settings.

Finding out the input methods of measuring the electroacoustic performance of the

telecoil of a hearing aid, that is, „teleboard‟ or „telewand‟ that would result in better

speech performance.

Method

Participants

15 adult‟s subjects in the age ranging from 15 to 55 years of age (mean age of 34.13

years), native and fluent speakers of Kannada participated in the study. They had an acquired

sensorineural hearing loss ranging from moderate to moderately-severe degree in the test ear.

Instrumentation

1. A calibrated diagnostic sound field audiometer was used for estimation of pure tone

thresholds, unaided and aided performance.

2. A CD player connected to a calibrated sound field audiometer for playing the speech material

in the unaided and aided testing condition.

3. A calibrated middle ear analyzer used for confirming normal functioning of the middle ear.

4. A digital behind-the-ear hearing aid with programmable telecoil, with a fitting range to suit

the degree of hearing loss of the participants. Appropriate sized ear tips to fit the test ears of

the participants were used.

5. A calibrated hearing aid analyzer to measure the root mean square (RMS) output of the

hearing aid in the microphone mode and for evaluating the electroacoustic performance using

both teleboard and telewand option.

6. Hipro and a personal computer with a soft ware to program the digital hearing aid.

7. Two landline telephones, one for sending and one for receiving the speech material.

Speech material used

Four different lists of phonemically balanced Kannada words developed by Yathiraj and

Vijaylakshmi (2005) were recorded onto an audio CD. The recorded word lists were presented at

a moderate level approximating the normal conversational level through the CD player via the

telephone. The telephone receiving the speech material was held/oriented by the participant in


44

such a way that it provided the best signal. This was achieved by asking the participant to adjust

the placement of the telephone during an informal talk over the telephone prior to beginning with

the test material.

Instructions

The participants were instructed to repeat the words they heard during the testing in free-

field condition with the hearing aid in microphone mode and over telephone in telecoil mode.

Test environment

The test was conducted in a sound treated double room with ambient noise levels within

permissible limits for testing in microphone mode. A quiet environment, free of electromagnetic

disturbances - especially those caused by fluorescent lights and a power line was used for testing

in the telecoil mode.

Procedure

Puretone thresholds were obtained using modified Hughson-Westlake procedure (Carhart

& Jerger, 1959), across octave frequencies from 250 to 8000 Hz for air conduction and 250 to

4000 Hz for bone conduction. Tympanometry and reflexometry were done to rule out any middle

ear pathology. The testing procedure consisted of the following five stages:

Stage I: Pre-selection and programming of the hearing aid in the microphone mode

The digital hearing aid was connected through a Hipro to the Personal Computer (PC)

that had the software for programming. After the hearing thresholds were fed into the software

(NOAH 3.0 and Connex 5), the digital hearing aid was programmed based on the NAL- NL1

prescriptive procedure. The gain at different frequencies was set as per the hearing loss of each

participant by fine tuning the hearing aid in microphone mode. Different program settings such

as listening in quiet for program 1 and telecoil mode for program 2 were activated. This was

done for each participant.

Stage II: Measurement of the output of the hearing aid in microphone or acoustic mode

and measurement of the speech recognition scores

The output characteristic of the hearing aid was measured with the help of a hearing aid

analyzer in the microphone mode. The participant was seated comfortably in the sound treated

audiological test room. The speakers of the audiometer were located at one meter distance from

the participant at 45° Azimuth from the test ear. The Speech Recognition Scores (SRS) for

Kannada PB word lists (Yathiraj & Vijaylakshmi, 2005) for each participant was noted down in

the unaided sound field and aided sound field conditions.

Stage III: Programming the telecoil of the digital behind-the-ear hearing aid in default and

modified settings

The hearing aid was programmed in two settings for the telecoil program:


45

As suggested by the programming software when the audiogram of a particular configuration was

plotted using prescriptive formula given by NAL-NL1. This was referred to as the „default‟ program

of the telecoil.

With „modified‟ settings based on the NAL-NL1 and on the basis of the feedback given by the

participant, that is the „modified‟ program of the telecoil. The gain with respect to different

frequencies was increased in the „modified‟ program such that the gain in the T-mode almost matched

with that of the target gain curve in the microphone mode. That is, the gain in the telecoil mode was

matched as close as possible to that of the target gain in the acoustic mode.

For each participant electroacoustic performance and speech recognition scores were

measured in the „default‟ and „modified‟ telecoil settings.

Stage IV: Measurement of electroacoustic performance in default and modified settings,

with teleboard and telewand

Electroacoustic measurement with the two program settings (i.e., default and modified)

was carried out. Teleboard and telewand were used as the input for creating the magnetic field

while carrying out electroacoustic measurements. The hearing aid analyzer was used for the

purpose. The sound chamber of the hearing aid test system has a telecoil board that was used to

measure the hearing aid performance with telecoil setting. The telewand is a device that is

supposed to provide a more realistic test of the telecoil features of a hearing aid than the

teleboard because it more closely simulates the magnetic field strength produced by a telephone

receiver. The telewand was connected to hearing aid analyzer instead of the teleboard to serve as

input to the hearing aid.

Stage V: Measurement of the Speech Recognition Scores (SRS) over the telephone with

hearing aid telecoil programmed to default and modified settings

The performance of the participants, in terms of SRS, over the telephone was evaluated in

the following two conditions:

1. Aided, over telephone, the telecoil of the hearing aid programmed to „default‟ setting.

2. Aided, over telephone, the telecoil of the hearing aid programmed to „modified‟

setting.

In the first condition, the speech recognition score was obtained with the hearing aid in

the telecoil mode, set at default program. The participant was asked to repeat the words heard

over the telephone. The number of words repeated correctly was scored. Each word repeated

correctly was given a score of one; the maximum score being 25, as the list consisted of 25

words. In the second condition, the speech recognition score was obtained with the hearing aid in

the telecoil mode set at the modified program. Similar procedure as in second condition was

followed and the responses were scored. The first and the second conditions were repeated for all

the participants.

These five stages were repeated for all participants for data collection. The data was

subjected to statistical analysis.


46

Results and Discussion

To investigate the aims of the present study, statistical analysis using SPSS software

(version 10.0) was carried out for the data obtained. The following statistical analyses were

carried out:

1. Comparison between Moderate and Moderately-Severe Groups

The following table (Table1) shows the mean and standard deviation values of SRS and

RMS (dBSPL) output for the participants in moderate and moderately-severe groups.

Table 1: Mean and SD values of SRS (max. score 25) and RMS output (dBSPL)

Table 1 depicts the mean and standard deviation (SD) values of SRS and RMS output (in

dBSPL). From the table it can be noted that the mean SRS was higher for subjects with moderate

hearing loss than for subjects with moderately-severe hearing loss in both the unaided and aided

conditions. The fact that individuals with greater degree of hearing impairment have more

difficulty in perception of speech has been well documented. The mean values of RMS output

were higher for the hearing aids programmed for moderately-severe hearing loss than that

programmed for moderate hearing loss. This is because for the moderately-severe hearing loss

category the target gain required was more than that needed for the moderate hearing loss

category.

The Mann Whitney U-Test (Non-parametric equivalent of independent t-test) was

performed to analyze the significance of difference between moderate and moderately- severe

Conditions

Mean & (SD)

Moderate

N=7

Mod.- Severe

(N=8)

SRS

(Max score = 25)

1. in unaided condition 10.71

(2.14)

8.75

(1.49)

2. with HA in microphone

mode

23.71

(1.25)

22.38

(2.26)

3. with HA in T-coil default 18.14

(3.13)

15.88

(2.53)

4. with HA in T-coil modified 22.00

(2.45)

20.63

(2.62)

RMS output

(dB SPL)

1. HA in microphone mode 92.76

(5.57)

104.03

(4.18)

2. HA in T-coil default mode

with teleboard

65.66

(6.92)

68.38

(7.03)

3. HA in T-coil modified with

teleboard

79.27

(5.47)

85.25

(6.10)

4. HA in T-coil default

mode with telewand

77.66

(5.06)

78.88

(5.82)

5. HA in T-coil modified

with telewand

92.13

(5.03)

98.88

(4.79)


47

groups, in SRS and RMS output. The test revealed no significant difference, even at 0.05 level of

significance, between the mean values of SRS and RMS output, in moderate and moderately-

severe groups. Hence, for further analysis, the scores of the subjects with moderate and

moderately-severe degree of hearing loss were combined to form one single group. Table 2

depicts the mean and standard deviation values of SRS when the groups were combined. The

Table 2 shows that the mean SRS values in the unaided condition was the lowest and those in the

aided conditions were higher. Among the aided mean SRS values the SRS was highest in

microphone mode and least when the telecoil was programmed to „default‟ mode.

Table 2: Mean and SD values of SRS (max. score = 25) when scores from moderate and

moderately-severe groups were combined (N = 15) in different conditions

Conditions Mean SD

Unaided SRS in free field 9.67 2.02

SRS with HA in microphone mode 23.00 1.93

SRS with HA in telecoil default mode 16.93 2.96

SRS with HA in telecoil modified mode 21.27 2.55

2. Comparison between SRS in different conditions, i.e., unaided SRS, SRS with hearing

aid in microphone mode, SRS with hearing aid in telecoil default mode and SRS with

hearing aid in telecoil modified mode

15151515N =

HA-Telecoil Modif ied

HA-Telecoil Default

HA-Microphone Mode

Unaided SRS

30

20

10

0

Fig.1: Mean SRS, with Confidence Interval of 95% SRS values, in unaided and aided

(microphone, telecoil default and telecoil modified) conditions

One-way repeated measures analysis of variance (ANOVA) was administered to check

the significance of difference between unaided condition, hearing aid in the microphone mode,

hearing aid in the telecoil default mode and hearing aid in the telecoil modified mode. A

significant interaction was found, with F (3, 42) = 325.87, p< 0.01. Bonferroni‟s multiple

Unaided Microphone Telecoil default Telecoil

modified

Hearing Aid Conditions

Mea

n S

RS

an

d 9

5%

CI

Co

nfi

de

ncI

nte

rval


48

comparison test was carried out to see the pair-wise differences. It revealed that all the

conditions, i.e., unaided SRS, SRS with HA in microphone mode, SRS with HA in telecoil

default mode and SRS with HA in telecoil modified mode when compared individually with

each other and all the conditions were significantly different from one another at 0.01 level of

significance.

The Figure 1 shows that among the aided conditions, the microphone mode had the

highest mean SRS values followed by the telecoil modified mode and then the telecoil default

mode. The unaided condition had the lowest mean SRS value. The reason for poorer SRS with

the hearing aid in telecoil default mode is that when the telecoil is in the default mode there is a

poor inductive coupling, especially in the low frequencies. Yanz and Preves (2003) have also

reported that inductive coupling is better in the high frequencies than in the low frequencies.

Chowdhury, Manjula and Abraham (2007) found similar results to that of Yanz and

Preves (2003). They found that the inductive coupling was poorer in the low frequencies and

hence gain should be increased in the low frequencies for better inductive coupling and thus

better SRS. Although in the present study the SRS in the telecoil modified mode were never

better than or equal to the microphone mode, in most of the cases, the scores in the telecoil

modified mode almost equated to that in the microphone mode. This could be because the

transmitting frequencies through the telephone is different and hence requires appropriate

changes in the „telecoil modified‟ program in order to equate the performance to that of the

hearing aid microphone mode.

Table 3: Comparison of SRS within different pairs of SRS in aided condition using microphone

and telecoil (default and modified) settings

SRS in Correlation

(r)

Paired difference

in Mean SRS

t(14)

Pair 1 HA-Microphone Mode -

HA-Telecoil Default

0.63** 6.07** 10.02

Pair 2 HA-Microphone Mode -

HA-Telecoil Modified

0.77** 1.73** 4.13

Pair 3 HA-Telecoil Default -

HA-Telecoil Modified

0.88** -4.33** -12.01

Note: ** p < 0.01

Table 3 depicts the results of the paired t-test. The test revealed that although the pairs

were highly correlated there was a significant difference between each pair at 0.01 level of

significance. It was observed that in pair 1 (Hearing aid microphone mode and Hearing aid

telecoil default mode) there was greater mean difference than in pair 2 (hearing aid microphone

and hearing aid telecoil modified mode). But when the telecoil gain in the modified setting was

increased and matched to the target gain curve of the microphone mode, the SRS improved. The

mean difference of the SRS in the microphone and the telecoil modified condition reduced. Thus,

from the above findings it can be concluded that increasing the gain, especially in the low


49

frequency region, of the telecoil can lead to better SRS. Hence it is recommended that the

telecoil gain be manipulated in order to achieve better speech recognition scores while using

telephone.

3. Comparison within pairs of RMS Output of the Hearing Aid Programmed in Different

Modes and Settings:

Table 4: Comparison of selected pairs of RMS output of hearing aid in different conditions

RMS output

of HA in

Pairwise comparison t(14)

1. Microphone vs. Teleboard default mode 15.69**

2. Microphone vs. Teleboard modified mode 8.19**

3. Microphone vs. Telewand default mode 10.77**

4. Microphone vs. Telewand modified mode 1.72

5. Teleboard default vs. Teleboard modified mode 5.76**

6. Telewand default vs. Telewand modified mode 8.08**

7. Teleboard default vs. Telewand default mode 9.95**

8. Teleboard modified vs. Telewand modified mode 10.93**

Note: ** Significant at 0.01 level

The results of the paired t-test revealed that all eight pairs were significantly different at

0.01 level of significance, except for the Pair 4, that is, RMS output in microphone mode versus

RMS output in telecoil modified mode, with telewand as the input source. That is, the RMS

output in the telecoil modified mode almost equated that in the microphone mode when the

measurement was made with telewand as the input.

4. Test of Significance of Correlation Coefficient between RMS Output and SRS

The relationship between the RMS output in different hearing aid settings and the SRS in

the respective hearing aid settings was measured using Pearson‟s correlation coefficient (r).

Table 5: Pearson‟s correlation coefficient (r) value between RMS output (dBSPL) and SRS in

different hearing aid (HA) settings

RMS Output of HA in SRS with HA in r

Microphone mode Microphone mode -0.30

Telecoil default (Teleboard) Telecoil default 0.30

Telecoil default (Telewand) Telecoil default 0.29

Telecoil modified (Teleboard) Telecoil modified -0.25

Telecoil modified (Telewand) Telecoil modified -0.12

It was found from the Table 5 that there was low correlation that was not significant

between the RMS output value and SRS in different hearing aid settings. That is, with increase in

the RMS output of the hearing aid, there was no increase in the performance of the participants

in their speech recognition scores at different settings of the hearing aid. The phenomenon called

speech level distortion which states that not only audibility but also speech perception ability of

the individuals with hearing impairment gets affected due to due high levels of presentations. In


50

such conditions, just a 10 to 20 dBSL may yield a better speech recognition score but further

increase may actually lead to poor speech intelligibility. Hence, the findings may be attributed to

this phenomenon.

Table 6: Pearson‟s correlation coefficient (r) value between RMS output of the hearing aid in

telecoil default and modified mode using teleboard and telewand

Note: ** Correlation is significant at 0.01 level

It was found from Table 6 that there was a highly significant correlation between the two

pairs of RMS output using teleboard and telewand in the default and modified settings. That is,

the increase in RMS output with teleboard was reflected in the increase in RMS output with

telewand. However, the RMS output measured using telewand was always slightly higher than

that measured with teleboard. The reason for this increase in the RMS output using telewand is

that the telewand is a device that is supposed to provide a more realistic simulation of the telecoil

features of a hearing aid than the built-in telecoil board in the sound chamber because it more

closely simulates the magnetic field produced by a telephone receiver.

To recapitulate the findings, it is inferred that the data from moderate and moderately-

severe groups when tested in the different aided conditions using Mann Whitney U-Test showed

no significant difference between the groups. In view of the main aim of the study that was,

whether it was telecoil default mode or the modified mode that gives the higher SRS, it was

found that the participants performed significantly well in the telecoil modified mode compared

to the telecoil default mode. This was evident from the mean and standard deviation values of

SRS between these modes. Next, a comparison of RMS output of hearing aid in different modes

was made using paired t-test. This revealed that all the pairs were significantly different at 0.01

level of significance, except for one, that is, RMS output of microphone versus RMS output of

the telecoil modified using telewand as input magnetic source.

To evaluate the second aim of the study, Pearson‟s correlation between the RMS output

and the SRS in the different hearing aid settings was performed. It revealed that there was no

correlation between the RMS output value and the SRS in any of the settings of the hearing aid.

References

Carhart, R. & Jerger, J. (1959). Preferred method for clinical determination of pure tone thresholds.

Journal of Speech and Hearing Disorders, 24, 330-345.

Compton, C. (1994). Providing effective telecoil performance with in-the-ear hearing instruments. The

Hearing Journal, 47, 23-26.

Chowdhury, S., Manjula, P. & Abraham, K., (2007). Programming Modifications for Optimal Inductive

Coupling in Hearing Aids. Presented in Indian Speech and Hearing Association, 39th Annual

Conference, January 19-21, Kerala, Calicut.

RMS Output in RMS Output in r

Telecoil default (Teleboard) Telecoil default (Telewand) 0.77**

Telecoil modified (Teleboard) Telecoil modified (Telewand) 0.71**


51

Davidson, S.A. & Noe, C.M. (1994). Digitally programmable telecoil responses: Potential advantages for

assistive listening device fitting. American Journal of Audiology, 3, 59-64.

EIA Standards RS-504 (1988). Magnetic Field Intensity Criteria for Telephone Compatibility with

Hearing Aids. Washington, DC: Electronic Industry Association.

Kochkin, S. (2002). Marke Trak VI: Consumers rate improvements sought in hearing

instruments. Hearing Review, 9, 18-22.

Levitt, H. (2001). The nature of electromagnetic interference. Journal of American Academy of

Audiology, 12, 322-326.

Lybarger, S. (1947). As cited in, Yanz JL, Preves D. (2002), Telecoils: principles, pitfalls, fixes, and the

future. Seminars in Hearing, 24, 1:29-41.

Revit, L. (1996). Proper use of telecoils: it‟s as easy as 1, 2, 3. . . 4! Available at

www.frye.com/library/application/larry.html

Ross, M. (2005). Telecoils: Issues and Relevancy. Seminars in Hearing, 26, 2, 99-108.

Skinner, M.W. (1988), Hearing Aid Evaluation. Englewood Cliffs. NJ: Prentice Hall, 222-223.

Smith, G. (1971). Coupling hearing aids to the telephone. The Volta Review 1, 47-50.

Takahashi, G. (2005). Programming the Telecoil: A Case Study. Seminars in Hearing, 26, 2:109-113.

Yanz, J.L. & Preves, D. (2003). Telecoils: principles, pitfalls, fixes and the future. Seminars in Hearing,

24, 29-41.

Yathiraj, A. & Vijaylakshmi, C.S. (2005). Phonemically Balanced word list in Kannada. Developed in

Dept. of Audiology, AIISH.

http://www.frye.com/library/application/larry.html


52

Estimation of Auditory Thresholds in Cochlear Implant Subjects

Using ASSR

Dayal Goswami & Rajalakshmi K

Abstract

The aims of this work were to characterize the electrophysiologic response obtained by

measurement of the Auditory Steady State Response (ASSR) in patients with a cochlear implant

and to study the relationship between the subjective thresholds of the implantees and those

estimated using acoustical auditory steady-state response -based objective audiometry. Nine

subjects were examined with the use of four carrier frequencies--500, 1000, 2000 and 4000 Hz--

modulated at frequencies between 78 and 95 Hz. Free field behavioral threshold estimation was

carried out using standard test protocols. The results revealed that there was a good correlation

between the acoustical ASSR and behavioral thresholds. In addition there was no statistical

difference between the two data, suggesting acceptable accuracy of behavioral threshold

estimation with the use of ASSR. Thus, ASSR technique shows great promise as a way to assess

auditory sensitivity in subjects with cochlear implants who cannot reliably respond on

behavioral testing. The results of the present study also suggests need for an in depth

investigation into efficacy of some measurement of supra threshold processes which would be

much more helpful in terms of monitoring device performance and adjust mapping. Finally the

results need to be confirmed in a greater number of subjects, not only for further validation of

the method, but also to acquire sufficient data to support the development of an expert system,

allowing the automated assessment of cochlear implantees and the programming of these

processors. The present study highlights the potential implications of ASSR instead of behavioral

methods in fitting of young children and other difficult-to-test to test patients.

Introduction

Scope of cochlear implantation is changing with increased emphasis on early

identification and remediation of hearing loss and the establishment of newborn hearing

screening programs throughout the world. This has increased the need for reliable, objective

techniques for determining candidacy and evaluating cochlear implant efficacy in infants and

very young children. The measurement of auditory thresholds or comfort levels for HI subjects

with cochlear implants currently requires their attention and active cooperation. Unfortunately,

subjective methods are of little or no value for the assessment of very young children and other

difficult- to-test population. The field of clinical objective audiometry has recently gained a new

technique promising to be a valuable addition to the AEPs test-battery. The ASSR evoked by

continuous amplitude modulated or mixed modulated tones, demonstrates unique characteristics


e-mail:[email protected]


53

developed primarily to address many of the limitations presented by the most widely used AEP,

the auditory brainstem response (ABR). While the 40 Hz responses initially kindled interest, its

application has been limited by its susceptibility to state of consciousness (Hall, 1992). A faster

modulation rate of between 75–110 Hz is not significantly affected by sleep or sedation

representing essentially the same generators as the auditory brainstem response (ABR) (Lins,

Picton & Picton, 1995). These higher rates are suitable for audiometric purposes across

populations (Lins, Picton, Boucher et al., 1996; Rickards et al., 1994). ASSR can be used for

assessing the cochlear implant candidacy. Swanepoel and Hugo (2004) studied the estimations of

auditory sensitivity for young cochlear implant candidates using the ASSR. Preliminary results

indicate that absent ABR and behavioral thresholds do not preclude the possibility of residual

hearing, making the ASSR a primary source of information regarding profound levels of hearing

loss as ASSR can be measured even for 120 dBHL signal.

ASSR provides attractive features, making this response of potential interest in the

assessment of cochlear implant function. It is also shown that there is a relationship between the

thresholds estimated objectively via electrical ASSR measurement and the subjective thresholds

of cochlear implantees (Menard et al., 2004). In determining post implant audiogram and to

assess speech perception through cochlear implant by objective audiometry, ASSR is very

useful. This information may be helpful in mapping process and post implant therapeutic

rehabilitation and management.

The threshold estimation is very important in diagnostic as well as rehabilitative

audiology. Auditory evoked potential particularly suited to frequency-specific measurements is

the ASSR to assess clinical populations in whom behavioural measures, speech detection and

discrimination are difficult to obtain (e.g., infants, children and difficult to test population).

Several studies stated that auditory steady state responses could be used to estimate the

frequency specific auditory sensitivity as accurate as other electrophysiological tests like ABR.

These studies reported that there was a good correlation between behavioral thresholds and

estimated ASSR thresholds.

Over the years, many studies have demonstrated that steady state response to modulation

frequencies 75-100 Hz can provide reliable estimate of hearing thresholds in children and adults.

In general the 80 Hz response can be recognized at 15 dB above hearing threshold. Rance and

colleagues (1995) predicted hearing thresholds using ASSR in a sample that include children and

adults who had sensorineural hearing loss that was of moderate to profound degree. ASSR

thresholds were estimated using tones with mixed modulation frequency of 90 Hz for carrier

frequencies 250 to 4000 Hz. Correlation between pure tone and ASSR thresholds was 0.96 for

250 Hz and as high as 0.99 for 2000 and 4000 Hz. The difference between ASSR threshold and

behavioral threshold decreased with increase in degree of hearing loss.

ASSR gained a wider acceptance as a clinical tool after Rance et al. (1998) demonstrated

its advantage in determining residual hearing thresholds for those infants and children from

whom ABR could not be evoked (at 100 dBnHL) using click stimuli. ASSRs were obtained


54

using mixed modulation for stimulus frequency at 250 to 4000 Hz with modulation frequency of

90 Hz. In a sample of 109 children, whose hearing loss ranged from moderate to profound, the

average discrepancy between ASSR and behavioral thresholds was only 3 to 6 dB (with standard

deviation of 6 to 8) with larger discrepancies and standard deviation found at 250 Hz and 500 Hz

as in previous studies. ASSR thresholds were within 20 dB of pure tone thresholds for 99 % of

comparisons and less than 10 dB for 82 % of subjects.

Cone-Wesson, Dowell, Tomlin, Rance and Ming (2002) reported the findings of their

study in which the threshold estimates from ASSR tests are compared to those of click- or tone

burst-evoked auditory brainstem responses (ABRs). The first, a retrospective review of 51 cases,

demonstrated that both the click-evoked ABR and the ASSR threshold estimates in infants and

children could be used to predict the pure-tone threshold. The second, a prospective study of

normal hearing adults, provided evidence that the tone burst-evoked ABR and the modulated

tone-evoked ASSR thresholds were similar when both were detected with an automatic detection

algorithm and that threshold estimates varied with frequency, stimulus rate and detection

method. The study illustrates that ASSRs can be used to estimate pure-tone threshold in infants

and children at risk for hearing loss and also in normal hearing adults.

There is an imperative need to estimate the improvements in auditory thresholds and

evaluate the benefit of achieving normal auditory behaviors using frequency specific objective

audiometry in cochlear implant subjects. It would assist objectively in fitting, accurate

programming and post-operative evaluation of cochlear implants in young and difficult-to-test

population by providing frequency specific information. ASSR stimuli are similar to speech

stimuli so this can objectively assess the speech perception abilities (validating the cochlear

implant fitting by showing that speech stimuli across the speech spectrum evoke a neural

response and therefore likely to be perceived by the subject). The outcomes of this study would

also document the efficacy of sound-field ASSR in estimating behavioral thresholds in children

with CI.

Aim:

The present study aimed at determining the auditory thresholds in cochlear implant

subjects using Auditory Steady State Responses and compares it with behavioral thresholds so

that this technique may be useful for young cochlear implantees to whom behavioral thresholds

could not be obtained.

Method

Participants: In total 9 subjects (3 females & 6 males) who used cochlear implant system in

one ear participated in this study. Their age ranged between 4-15 years. The subjects were

recruited from the Listening Training Unit, Dept of Audiology, AIISH, Mysore. They are

continuing listening therapy after implant for 1 to 4 years duration. They have a recent and stable

mapping. The descriptive data of these children are given in Table 1.


55

Instrumentation: Calibrated diagnostic two channel audiometer was used for estimation of

auditory thresholds for frequencies 500 Hz to 4000 Hz in free field set-up. GSI Audera ASSR

(Version 1.0.2.2) was used for recording ASSR.

Test environment: All the measurements were carried out in an acoustically treated double

room situation. The ambient noise levels were within the permissible levels according to ANSI

(1991).

Procedure: Sound field audiometry

Free field behavioral threshold estimation was carried out in sound treated rooms using

standard test protocols. For this measurement FM tones ranging from 500 to 4000 Hz were

presented through calibrated loudspeakers.

Table 1: The descriptive data of all the children participated in the study

Ser

ial

Nu

mb

er

Age/

sex

Ear

of

imp

lan

tati

on

Age

of

imp

lan

tati

on

Du

rati

on

of

CI

use

d

Str

ate

gy

Con

tou

r or

stra

igh

t

Mod

e o

f

stim

ula

tion

No o

f act

ive

elec

trod

e

inse

rted

C

om

pan

y

1 7yrs/M L 5.5 yrs 1.5yrs ACE Contour Monopolar 22 N 24

Freedom

2 6 yrs/M R 4 yrs 2 yrs ACE Contour Monopolar 22 N 24

3 15yrs/M R 11 yrs 4 yrs ACE Contour Monopolar 22 N 24

4 4.5 yrs L 4 yrs 0.5 yrs ACE Straight Monopolar 22 N 24

Freedom

5 7 yrs/M R 6.5yrs 0.5 yrs ACE Contour Monopolar 22 N 24

6 7yrs/M L 6yrs 1yr ACE Contour Monopolar 22 N 24

7 7yrs /F R 5.5yrs 1.5 yrs ACE Contour Monopolar 22 N 24

8 7yrs/F R 5yrs 2 yrs ACE Contour Monopolar 22 N 24

9 7.5yrs/F R 6.5yrs 1 yr ACE Contour Monopolar 22 N 24

The ISO 8253-3 standard prescribes a loudspeaker set-up as shown in figure 1. The

participant was positioned on an axis in front of the loudspeaker from which the test signal is

emitted (shown on figure1). Noise was emitted from two loudspeakers placed symmetrically at a

45o

angle on each side of the subject. The loudspeaker was placed in level with the head of the

subject in sitting position. The speaker faced towards the reference point which was defined as

the middle point of a straight line between the openings of the subject‟s ear canals. The distance

between the reference point and the loudspeaker was 1 m.


56

ASSR: Recording of Auditory Steady State Response: ASSRs were recorded using the test

protocol given in the Table 2.

Table 2: ASSR stimulus and recording parameters

Stimulus Recording

Stimuli: AM/FM tones Electrode montage: FPz (+), Cz (-)

and ground on neck.

Carrier Frequency: 500, 1K, 2K and 4KHz Subject state: awake

Modulation frequency: 78, 81, 88, 95 Hz Number of samples: maximum of 64

Modulation depth: 100% AM & 10% FM

Transducer: loudspeaker at 45 degree angle

Thresholds were obtained using a bracketing approach. At higher intensities 10-20 dB

steps were used and at lower intensities 5dB steps were used to vary the intensity. The testing

was carried out in only in one ear implanted ear. Then threshold was defined as the minimum

level at which the phase coherence was significant.

Results

The ASSR determined thresholds and measured behavioral thresholds were statistically

analyzed using descriptive statistics and linear regression. Statistical evaluations were carried out

using SPSS for windows (Version 14.0).


57

Initial calculations assessed the mean and standard deviations of the two different

measures i.e., behavioral threshold and auditory steady state responses (ASSR) or ASSR

thresholds. The Table 3 shows mean and standard deviations of ASSR and Behavioral thresholds

at all the test frequencies.

Table 3: Mean and SD of ASSR thresholds, behavioral thresholds at each test frequency

Frequency (Hz) ASSR threshold (dB HL) Behavioral threshold (dB HL)

500 33.89 ± 4.859 25.56 ± 4.640

1000 36.11 ± 7.407 25.56 ± 4.640

2000 32.78 ± 7.949 24.44 ± 4.640

4000 38.33 ± 7.906 26.67 ± 5.000

.

0

5

10

15

20

500 1k 2k 4k

Frequency (Hz)

AS

SR

-Beh

avio

ral t

hre

sho

ld (d

B)

Figure 2: Mean differences between auditory steady state responses and behavioural thresholds

at each test frequency. Error bars represent the standard error of mean.

It can be observed in the figure 2 that the mean differences are more for 4 KHz compared

to other frequencies and it is less for 2 KHz. There was a good correlation (p<0.001) between

ASSR thresholds and behavioural thresholds. Independent t-test was run to test the significant

difference between behavioral thresholds and ASSR thresholds. No significant differences were

found between two groups. Although the mean data did not reach the significance, the difference

between behavioral threshold and ASSR threshold does exist.

Table 4: The correlation and significance values between the ASSR thresholds and behavioral

thresholds at each test frequency

Frequency Pearson‟s correlation Significance

500 Hz 0.862 0.001**

1000 Hz 0.798 0.010**

2000 Hz 0.894 0.001**

4000 Hz 0.632 0.34*

**. Correlation is significant at the 0.001 level (2-tailed)

*. Correlation is significant at the 0.05 level (1- tailed)


58

Table 5: t-value and level of significance between behavioral thresholds and auditory steady state

response thresholds at each of the test frequencies

Frequency (Hz) t- Value Significance

500 2.931 .430

1000 0.638 .220

2000 2.326 .127

4000 0.636 .099

Linear regression analysis was performed at each of the test frequencies to predict

behavioural thresholds from ASSR thresholds. Linear regression curves for 500, 1000, 2000 and

4000 Hz and combined for all frequencies are shown in figures 3, 4, 5, 6 and 7 respectively. In

figure 3 through 7 linear regressions is shown as the solid line. Dotted line represents equal

values in dB HL. Correlation coefficients (r), regression equations, and standard error of

regression (se) are shown in the upper left of each graph.

Figure 3: Relationship between ASSR thresholds (x axis) and behavioural thresholds (y axis) at 500 Hz



59



Figure 7: Relationship between ASSR (x axis) & behavioural thresholds (y axis) at all the test frequencies

Dotted lines represent equal values in dB HL. Linear regression is shown as the solid

lines. Correlation coefficients (r), regression equations and standard error of regression (se) are

shown in the upper right of each graph.


60

Figure 8: Estimated behavioural thresholds and with actual measured behavioural thresholds at 500 Hz

Figure 9: Estimated behavioural thresholds and actual measured behavioural thresholds at 1000 Hz

Figure10: Estimated behavioural thresholds and with actual measured behavioural thresholds at 2000 Hz


61

Figure 11: Estimated behavioural thresholds and actual measured behavioural thresholds at 4000 Hz

As can be seen in the graphs 8 through 11 the AUDERA estimated behavioral thresholds

are significantly correlated with actual measured behavioral thresholds.

Discussion

The aim of the study was to estimate the auditory thresholds in cochlear implanted

children using an objective technique (auditory steady state responses) and compare that with

behavioral thresholds.

Comparison of behavioral and ASSR threshold

The ASSR thresholds for the subjects with cochlear implant obtained in the present

steady are higher than the measured behavioral thresholds. The results of the current study are

similar to some of the earlier investigators with normal and hearing impaired population (Aoyagi

et al., 1994; Rance et al., 1995; Rickards et al., 1994). The difference between ASSR threshold

and behavioral threshold was lower in subjects with hearing loss than in normals. This may be

attributed to softness imperceptions or recruitment (Rance et al., 1995).

The difference between ASSR threshold and behavioral threshold was higher at high

frequency compared to that of low frequency. These findings are not in consistence with the

earlier findings showing strong correlation at high and poor correlation at low frequencies in

hearing impaired population (Aoyagi et al., 1994a; Rance et al., 1995; Rickards et al., 1994). The

poor correlation at low frequencies could be because of normal biological and environmental

noise which centers on low frequency that might affect ASSR measurement at lower frequencies.

Strength of prediction

Truy et al. (1998) using other electrophysiological methods to estimate behavioral

thresholds observed linear decrease in strength of prediction as test frequency increases. In other

words, the prediction is more accurate at low frequencies compared to high frequencies. The

results of the present study followed the same trend as observed in Truy‟s (1998) study.

However, in the present study, linearity in prediction was not observed. Prediction at 2000 Hz

was the best of all the test frequencies.


62

The following explanations describe why prediction is high at low and mid frequencies

and vise versa. First, reduced dynamic range at high frequency compared to that at low

frequencies (Menard et al, 2004). Second, it can be hypothesized that as the current level

required is lower for low frequency so threshold prediction is better at low and mid frequencies

as compared to higher frequencies. This might be due to the larger neuronal survival of low and

mid frequency fibers leading to better synchrony. Third, Picton et.al (2003) reported that at

threshold level there is more jitter seen in neural responses and require more number of averages

for estimation of thresholds. As observed from the threshold (T) level of Cochlear implant (CI)

subjects participated in the present study, T levels are high at high frequencies as compared to

low and mid frequencies which would have contributed more threshold variations. However, it is

difficult to understand the basic physiology owing to less number of subjects in the present

study.

There was a significant correlation between ASSR and behavioral threshold and

correlation coefficient ranged from 0.632 to 0.894. ASSR detection involves only objective

procedures which restrict the audiologist‟s role. Sometimes artifactual responses may be

considered as response in objective procedures. This could lead to spurious results and hence

may be drawback for clinical use of ASSR. From the discussion it can be concluded that ASSR

>70 Hz are efficient in threshold prediction of CI population and estimating audiogram

configuration of the same population. However, the conclusions should be taken with caution as

the total number of participants was less. It is important to control the subject state while

recording ASSR for higher modulation frequency.

Conclusions

The results of the present study indicated that there is a good correlation between the

acoustical ASSR and behavioral thresholds. In addition accuracy of behavior threshold

estimation with ASSR in subjects with cochlear implants is acceptable. Thus ASSR technique

shows great promise as a way to assess auditory sensitivity in subjects with cochlear implants

who cannot reliably respond on behavioral testing. Moreover, the results of the present study

suggests need for an in depth investigation into efficacy of some measurement of supra threshold

processes which would be much more helpful in terms of monitoring device performance and

adjust mapping. Finally the results need to be confirmed in a greater number of subjects, not only

for further validation of the method but also to acquire sufficient data to support the development

of an expert system, allowing the automated assessment of cochlear implantees and the

programming of these processors. The present study highlights the potential implications of

ASSR instead of behavioral methods in fitting of young children and other difficult-to-test to test

patients.

References

Aoyagi, M., Kiren, T., Furuse, H., Fuse, T., Suzuki, Y., Yokota, M. & Koike, Y. (1994a). Pure

tone threshold predicted by 80 Hz amplitude-modulation following response. Acta-

otolaryngologica, (supplement-511): 7-14.


63

Aoyagi, M., Kiren, T., Furuse, H., Fuse, T., Suzuki, Y., Yokota, M. & Koike, Y. (1994b). Effects

of aging on amplitude-modulation following response. Acta-otolaryngologica,

(supplement-511):15-22.

Aoyagi, M., Suzuki, Y. M. Y., Furuse, H., Watanabe, T. & Tsukasa, I. (1999). Reliability of 80

Hz amplitude- modulation- following response detected by phase coherence. Audiology

and Neuro-otology, 4, 28-37.

Cone-Wesson, B., Parker, J., Swiderski, N. & Rickards, F. (2002). The auditory steady state

response: full-term and premature infants. Journal of the American Academy of

Audiology, 13, 260-269.

Hall III, J. W. (1992). Handbook of Auditory Evoked Responses, Boston: Allyn & Bacon.

Herdmann, A. T. & Stapells, D. R. (2003). Auditory steady-state response thresholds of adults

with sensorineural hearing impairments. International Journal of Audiology, 42, 237-254.

Lins, O. G., Picton, T.W. & Picton, E.W. (1995). Auditory steady state responses to multiple

simultaneous stimuli. Electroencephalography Clinical Neurophysiology, 96, 420-432.

Lins, O. G., Picton, T. W., Boucher, B. L., Durieux-Smith, A., Champagne,S.G., Moran, L. M.,

Perez-Abalo, M. C., Martin, V. & Savio, G. (1996). Frequency specific audiometry using

steady state response. Ear and Hearing, 17, 81-96.

Ménard, M., Gallego, S., Truy, E., Berger-Vachon, C., Durrant J. D. & Collet, L. (2004)

Auditory steady-state response evaluation of auditory thresholds in cochlear implant

patients. International Journal of Audiology, 43 (Suppl 1: S39-43).

Picton, T.W., Skinner, C.R., Champagne, S.C., Kellett, A.J. & Maiste, A.C. (1987). Potentials

evoked by the sinusoidal modulation of the amplitude or the frequency of the tone.

Journal of the Acoustical Society of America, 82: 165-178.

Picton, T. W., Durieux-Smith, A., Champagne, S. C., Whittingham, J., Moran, L. M., Giguère,

C. & Beauregard, Y. (1998). Objective evaluation of aided thresholds using auditory

steady-state responses. Journal of the American Academy of Audiology, 9, 315–331.

Picton, T. W., John, M. S. & Dimitrijevic, A. (2002). Possible role for auditory steady state

responses in identification, evaluation and management of hearing loss in infancy.

Audiology Today, 14, 29-34.

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65

A search to possible pathways for later peaks of VEMP and N3

potential

Deepashri Agrawal & Animesh Barman

Abstract

The VEMP is an inhibitory potential recorded from the sternocleidomastoid (SCM)

muscle in response to loud sounds. There are four peaks in VEMP which have been classified

according to their latencies, known as p13, n23, n34, p44. Waves p13-n23 which are saccular in

origin possibly and have been studied excessively due to the higher response rate in normals

whereas the N34- P44 which are believed to be cochlear origin have been scarcely explored thus

ignoring their clinical significance. There is another potential (N3 potential) which is thought to

be originated from vestibular system is the negative peak at 3 msec in ABR recording. The aim of

the study was to know any relation between the later peaks of VEMP and N3 potential and also

to explore the possible routes for generation of these potentials. Two groups of subjects

participated in the study. First group of subjects (control group) consisted of subjects in the age

range of 16 to 45 years, with normal hearing (N=30) and the second group, (experimental

group) consisted of 30 subjects with different configuration of sensorineural hearing loss. The

experimental group was further divided into three subgroups based upon their hearing loss.

Results revealed that all the four groups were significantly different in terms of presence of later

peaks of VEMP. One way ANOVA showed significant difference in all the four groups. Results

revealed that occurrence of later peaks of VEMP increased with increase in severity of hearing

loss. It was observed that in only 6.7% of the subjects when VEMP was absent N3 potential was

also absent. In 40% of the subjects when later peaks of VEMP were present N3 potentials were

also present suggesting that there might be some similarity in pathway between later peaks of

VEMP and N3 potential. Based on the results and literature available it was felt that there could

be three possible pathways for later peaks of VEMP, first via Vestibulo-cochlear anastomosis,

second through cochlear afferents and third via Olivocochlear bundle. Similarly for N3 potential

there could be two sites of origin first could be vestibular nucleus and other one could be

cochlear nucleus.

Key words: Later peaks of VEMP, N3 potential, Vestibulo-cochlear anastomosis, cochlear

nucleus, olivocochlear bundle

Introduction

The VEMP by definition is a short-latency electromyogram recorded from the tonically

contracted SCM in response to high-intensity acoustic stimulation (Bickford, Jacobson & Cody,

Lecturer in Audiology, All India Institute of Speech and Hearing, Mysore, India



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1964; Cody & Bickford, 1969; Colebatch & Halmagyi, 1994). Colebatch et al., (1994) labeled

the serial peaks P13, N23, N34 and P44, based on their latencies. The research studies have

almost solely investigated wave P13-N23 complex. In contrast, Colebatch, Halmagyi and Skuse

(1994) and Robertson and Ireland (1995) reported presence of N34-P44 peaks of VEMP in 60 to

68% of their normal hearing subjects interrupting the investigation of their clinical significance.

There is another potential which is thought of vestibular in origin and can be recorded

during the ABR recording. The evoked potential is known as N3 potential which is a large

negative deflection with latency of 3 ms (N3) and which has been recorded in patients with

peripheral profound deafness (Kato et al., 1998). The later peaks of VEMP are thought to be of

cochlear origin and N3 potentials were thought to be of vestibular origin though both of them are

elicited by acoustic stimulation. Thus it was essential to know the anatomical and functional

relationship between the cochlear and vestibular system which resulted in initial peaks of

VEMPs to be of vestibular origin and later peaks to be of cochlear origin.

When n34-p44 peaks recorded from the Sternocleidomastoid muscle are thought to be of

cochlear in origin this implies that auditory nerve needs to stimulate the vestibular nerve to elicit

responses from the Sternocleidomastoid muscle. Thus it indicates that later potentials are likely

to be absent or decreased in cases with hearing loss. However there are a few studies in which

n34-p44 potentials are present in profound hearing loss individuals (Ferber-Viart, Dubreuil &

Duclaux, 1999) which raised the question whether these potentials are really of cochlear origin.

This could be understood if the study is carried out in normal and in subjects with hearing loss.

Kato et.al., (1998) studied the N3 potential in profound hearing loss cases and presence of this

negative peak confirms vestibular system especially saccule as a site of origin whereas N34-P44

peaks of VEMPs recorded by stimulating the SCM muscle are thought to be cochlear origin.

Hence it suggested that there could be some relation between the two potentials. If there

is a relationship between the two then what could be the possible pathway for both later peaks of

VEMP and N3 potential? How these potentials can help in understanding Vestibulo-cochlear

nerve pathology?

To find out the answers for all these questions the present study was taken up with the

following aims:

To study the relationship between the severity of hearing loss and N34-P44 potentials of VEMP

To understand the relationship between N3 potentials and VEMP

To understand the possible route for later peaks of VEMP and the possible route for the N3 potential

To understand the structural and functional relationship between the Vestibulo-cochlear nerve root

Method

Subjects

The present study comprised of two major subject groups, the Control group and the Clinical

group. The Control group comprised of 30 (60 ears) normal hearing individuals in the age range


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of 16 to 45 years. The Clinical group consisted of 35 subjects with sensorineural hearing loss in

the age range of 16 to 45 years. This clinical group was further sub divided into three groups

based on their severity of hearing loss as:

Group A: 10 (20 ears) individuals with mild sensorineural hearing loss

Group B: 10 (20 ears) individuals with severe sensorineural hearing loss

Group C: 15 (30 ears) individuals with profound hearing loss

Subject selection criteria

Control group:

1. All the subjects had normal hearing sensitivity, having puretone thresholds within 15 dBHL

at frequencies from 250 to 8000 Hz in octaves, in both ears.

2. All of them showed „A‟ type tympanogram with normal reflexes in both ears

3. They did not have any history or presence of any otological problems

4. They reported no complaints of giddiness, vertigo, balancing problem, spondilitis and high

blood pressure

5. All the subjects had UCL (uncomfortable level) above 105dB HL

Clinical group:

1. Subjects with pure tone thresholds of varying degrees with sensorineural hearing loss were

chosen.

2. Attempts were made to rule out space occupying lesions based on ABR results or

neurological assessment as and when it was required.

3. They had „A‟ type tympanogram with presence, elevated or absence of acoustic reflexes in

both the ears.

4. Subjects did not have any history of middle ear pathology.

5. Subjects had UCL above 105 dBHL, as confirmed by UCL testing.

Instrumentation:

The vestibular evoked myogenic potentials and N3 potentials were recorded using IHS smart EP

version 2.39 (Intelligent hearing system, Florida, USA) instrument

Procedure

Phase I: Routine evaluations for the selection of subjects

1. Detailed case history was taken for all the individuals to rule out any history or presence of any

otological problems, general weakness, giddiness, vertigo, high blood pressure and spondilitis.

2. The pure tone audiometric thresholds were obtained using modified version of Hugson and

Westlake procedure (Carhart & Jerger, 1959) with the help of GSI-61 Audiometer.

3. Tympanometry and acoustic reflexes were tested using GSI Tympstar to rule out the presence

of middle ear pathology.


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4. ABR was done by cleaning the electrode site with the help of skin preparing gel to rule out the

possibility of space occupying lesion.

Subjects who fulfilled the selection criteria either for control group and or for clinical group

were considered for the study.

Phase II: Experiment

VEMP: VEMPs were recorded for all the subjects in control and clinical group.

Subjects were instructed:

To sit straight and turn their head to opposite side of the test ear so as to stretch the Ipsilateral

Sternocleidomastoid muscle.

To close their eyes at the time of recording to avoid interference by occulomotor reflexes.

To avoid extraneous movements of head, neck and jaw to elude muscle artifacts.

Prior to the VEMP and N3 potential recording the electrode sites were cleaned using skin

preparation gel to reduce the impedance. The electrodes were placed on respective sites as given

in the table 1 and 2 for VEMP and N3 potential respectively with conducting paste to improve

the conduction. It was ensured that impedance was within 5 K ohms at each recording site and

inter electrode impedance was within 3 K ohms to obtain good responses.

The protocol proposed by Huang T., Young Y. and Cheng P. (2004) was used in the

present study to record VEMP which is given below:

Table 2: Depicts the parameters used for VEMP recording

N3 potential: N3 potentials were recorded for individuals with profound hearing loss.

Instructions given to the subjects were as follows:

1. Subjects were asked to sit in chair and close their eyes.

2. They were informed not to stretch their neck, instead were asked to sit quietly.

Electrode Montage

Inverting electrode Sternoclavicular joint

Non Inverting electrode Midpoint of SCM.

Ground electrode Forehead

Acquisition parameters

Analysis time 100 msec.

Filter setting 20-2000 Hz.

Amplification 50,000

Stimulus parameters

Type of stimulus Clicks

Repetition rate 5/sec.

Polarity Rarefraction

Intensity 105 dBnHL.

Stimulus duration 500 µsec.


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3. They were instructed to avoid extraneous movements of head, neck and jaw to elude muscle

artifacts.

Table 3: Depicts the parameters used to record N3 potential

Electrode montage

Non Inverting electrode Vertex

Inverting electrode Ipsilateral mastoid

Ground electrode Nape of the neck

Acquisition parameters

Analysis time 10 msec.

Filter setting 100 – 3000 Hz.

Amplification 10,000

Stimulus parameters

Type of stimulus Clicks

Repetition rate 10/sec.

Polarity Rarefraction

Intensity 95 dBnHL

Total no. of stimuli 500 stimuli.

Stimulus duration 100 µsec.

N3 potential was recorded using the protocol proposed by Toshihisa, Iwasakib, Takaib

and Takegoshic, (2005) as shown in the table above. For all the subjects VEMPs and N3

potential were recorded for right side first and then for the left side. It was ensured that each

recording was repeated to have reproducibility of the responses. For subjects in Group C, N3

potential was recorded after the VEMP recording.

Results

The data was statistically analyzed using One-way ANOVA, Duncan‟s post-hoc test, Chi-square

test and Cramer‟s V test. All the statistical analysis was carried out using SPSS 10 software.

1. Relationship between the severity of hearing loss and N34 – P44 potentials of VEMP:

Table 4: Depicts the Mean and SD of latencies and peak to peak amplitude of later peaks of VEMP

Entity No. Group Mean SD Min. Max.

N34

13 Mild 32.5538 3.1532 28.80 37.60

14 Severe 35.1714 2.2228 32.00 38.60

24 Profound 34.7937 3.0226 29.00 39.80

31 Normal 33.3161 3.1136 27.80 39.20

P44

13 Mild 42.6154 3.4024 37.60 47.20

14 Severe 46.0143 2.1260 43.00 49.80

24 Profound 44.8138 3.2994 38.20 50.00

31 Normal 43.7574 3.1351 38.40 49.00

PP

13 Mild 4.4885 2.2823 2.18 9.32

14 Severe 4.1950 1.5442 2.09 6.78

24 Profound 4.4579 1.8855 1.58 8.97

31 Normal 3.3110 2.7835 0.90 15.00


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Table shows that there is a slight variation in latency and peak to peak amplitude of N34

– P44 peak of VEMP with the varying degree of hearing sensitivity.

The One-way ANOVA was administered to check whether latency and peak to peak

amplitude are significantly different or not and if ANOVA was significant then Duncan‟s post-

hoc test was done to see significant differences between the groups of subjects. Results revealed

that control group and subgroups of clinical group were significantly different for latency N34

peak and P44 peak and not for peak to peak amplitude for later peaks of VEMP (p<0.05).

On Duncan‟s post-hoc test showed there was significant difference between the data

obtained from individuals with mild hearing loss from those with profound and severe hearing

loss and rest of the groups were not different for N34 peak of VEMP.

Table 5: Depicts the Duncan‟s post-hoc test results for N34 peak of VEMP

Groups No. of ears Subset for alpha = .05

1 2

Mild 13 32.5538

Normal 31 33.3161 33.3161

Profound 24 34.7937

Severe 14 35.1714

Sig. 0.443 0.079

For P44 peak of VEMP significant difference was observed between individuals with

mild hearing loss and with severe and profound hearing loss but not from individuals with

normal hearing, whereas individuals with normal hearing differed significantly from individuals

with severe hearing loss and not from individuals with mild and profound hearing loss (p<0.05).

Table 6: Depicts the Duncan‟s post-hoc test results for P44 peak of VEMP

Groups No. of ears Subset for alpha = .05

1 2 3

Mild 13 42.6154

Normal 31 43.7574 43.7574

Profound 24 44.8137 44.8137

Severe 14 46.0143

Sig. .270 .308 .247

Further data was analyzed to see if there is any association between the presence or

absence of N34- P44 wave and hearing sensitivity based on the data obtained. Chi square test

was administered and results revealed that there lies a significant association between the

presence of N34 – P44 wave of VEMP and increase in hearing sensitivity, χ2 (1) = 0.464,

(0.05<p<0.1).


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On Cramer‟s V test it was seen that association is 23% and the response rate to eliciting

wave N34-P44 from group with normal hearing sensitivity, mild, severe group and profound

hearing loss group were 51.7%, 65%, 70% and 80% respectively as seen in the following table.

Table 7: No. of ears and percentage of the presence or absence of later peaks of VEMP

Groups No. of ears Absent Present Total

Mild No. of ears 7 13 20

35.0% 65.0% 100.0%

Severe No. of ears 6 14 20

30.0% 70.0% 100.0%

Profound No. of ears 6 24 30

20.0% 80.0% 100.0%

Normal No. of ears 29 31 60

48.3% 51.7% 100.0%

Total No. of ears 48 82 130

36.9% 63.1% 100.0%

2. Relationship between N3 potentials and N34 – P44 peaks of VEMPs:

The later peaks of VEMP and N3 potential were recorded in individuals with profound

hearing loss. The mean and the standard deviation along with minimum and maximum values for

N3 potential latency and absolute amplitude are given in the table below:

Table 8: Mean, Standard deviation (SD), minimum and maximum values for N3 potential

latency and absolute amplitude in subjects with profound hearing loss

Parameters Mean SD Minimum Maximum

N3 3.3033 0.4782 2.28 4.05

Amplitude -0.2142 0.3941 0.22 -1.25

It was seen that N3 potential was recorded with a range was of 1.77 msec and for

absolute amplitude the range was 1.47 micro volts. The Chi-square test was done to see if there

lies any association between the presence and absence of N34-P44 peak of VEMP and presence

or absence of N3 potential. Chi-square test showed no significant association between the

presence and absence of the two potentials for χ2

(3) = 7.486, (p>0.05). On cross tabulation it

was evident that N3 potential was present in 4 ears when N34-P44 peak of VEMP were absent

where as 12 ears had absence of N3 potential with presence of later peaks of VEMP.

Form the table it is evident that only 6.7% of the subjects when VEMP was absent, N3

potential was also absent. And for 40% of the subjects when later peaks of VEMP were present,

N3 potentials were also present. Thus 46.7% of the population had similar test results and 53.3%

did not show the same findings


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Table 9: Distribution of data for presence/absence of later peaks of VEMP and N3 potential in

subjects with profound hearing loss

Parameter N3 Total

Absent Present

N34 –P44

No. of ears 2 4 6

Absent 6.7% 13.3% 20%

No. of ears 12 12 24

present 40% 40% 80%

Total

No. of ears 14 16 30

46.7% 53.3% 100%

These results are discussed to understand the possible root of VEMP and the physiological

relationship between the Vestibulo-cochlear nerve routes.

Discussion

The results of the present study have shown that there is association between presence of

later peaks of VEMP and severity of hearing loss. Chi-square test showed that there is

association of 23% between presence of N34- P44 wave of VEMP and severity of hearing loss.

Duncan‟s post-hoc test did not show any specific trend in increase or decrease of latencies and

amplitude of later peaks of VEMP in individuals with different hearing sensitivity. On the

Cramer‟s V test it was seen that in individuals with normal hearing sensitivity only 51% had

presence of N34-P44 peak of VEMP compared to 80% seen in individuals with profound hearing

loss. The initial findings reported in the literature by Colebatch et al. (1994) who could record

later peaks of VEMP from 60% of individuals with normal hearing, whereas Huang et al. (2004)

could record from 80% of the individuals with normal hearing sensitivity.

In the present study later peaks of VEMP could be recorded from 80% of the individuals

with profound hearing loss which is much higher than what has been reported in the literature by

Wu and Young in (2002). They could record later peaks of VEMP only from 45% of the

individuals with sudden hearing loss. It is also evident from the current study that as the severity

of hearing loss increased the percentage of presence of later peaks of VEMP also increased.

However, there are no such studies available in the literature which compared the presence of

later peaks of VEMP in population with different degrees of hearing loss.

In the current study the findings suggest that probably later peaks of VEMP may not be

cochlear origin as wave complex is present in 80% of individuals with profound hearing loss.

However, there are reports in literature which support the fact that later peaks of VEMP are

cochlear in origin as Colebatch et al., (1994) found presence of later peaks of VEMP in before

and after selective vestibular nerve section.

Taking these results together it might suggests that wave n34–p44 may have both a

cochlear and vestibular origin. The possible pathways for generation of N34- P44 peak of VEMP

are discussed below:


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The first possible pathway:

There are histopathological and morphological studies which have proven that the

(saccular nerve) inferior vestibular nerve links to the cochlear nerve in internal acoustic canal

and this intimate connection was named as Vestibulocochlear anastomosis (Oort, 1918;

Rasmussen, 1940; House, 1961; Kim et al., 1998; Nageris, Kalmanowitz, Segal & Frenkiel,

2000; Labrousse, Ouedraogo, Avisse, Chays & Delattre, 2005). It was also found that cochlear

afferent fibers go to the lateral ipsilateral vestibular nucleus (Cazals, Erre & Aurousseau, 1987)

may be via vestibulocochlear anastomosis. There are reports which suggest that vestibulospinal

nerve fibers from the medial and lateral vestibular nucleus descend down to the SCM muscle via

MVST and to leg muscle via LVST, Colebatch (1992 & 1994).

Pathway I Pathway II

Figure 1: possible pathways for generation of later peaks of VEMP

It can be explained that from the fig. 1 that there is a possibility of acoustic stimulation to

the cochlea stimulates the cochlear afferents which in turn might be stimulating vestibular

nucleus in the brainstem via vestibulocochlear anastomosis. From there impulses are sent to the

neck muscles via the medial vestibulospinal tract (MVST) and the leg muscles via the lateral

vestibulospinal tract (LVST).

Second possible pathway:

On the other hand the current study suggests that the wave n34-/p44 could also be

obtained in deaf ears, implying that they were probably not of cochlear afferent origin as WU

and Young (2002) observed the presence of later peaks of VEMP in 45% of subjects after sudden

hearing loss. This implies that these peaks might occur via a polysynaptic pathway also


74

terminating on the motor neuron of SCM muscles, Wilson et al. (1969), Murofushi, Halmagyi,

Yavor & Colebatch (1996) & Kushiro, Zakir, Sato, Ono, Ogawa and Meng (2000).

It can be seen from figure.1 that inferior vestibular nerve originates from saccule and

utricle and sends a few projections into the dorsal cochlear nucleus. Hence the possible pathway

could be from saccule to the inferior vestibular nerve fibres progress to the vestibular nuclei

which are responsible for generation of early peaks of VEMP, whereas few fibers progressed to

the cochlear nucleus. These few fibers later via the intimate connection between cochlear and

vestibular nucleus terminates in medial and lateral vestibular nuclei. From this vestibular nuclei

they innervate the SCM i.e. neck muscle via MVST and to leg muscle via LVST resulting in the

generation of later peaks of VEMP.

From the above discussion and information from the literature it may be concluded that

the above mentioned route could be the generator of later peaks of VEMP. This could be the

possible route as 80% of individuals with profound hearing loss showed presence of later peaks

of VEMP. Thus the longer latencies of later peaks could be due to the longer path travelled by

the nerve fibers to stimulate the neck muscle.

Third possible pathway:

There could also be a possibility of the third route for generation of later peaks of VEMP

via olivocochlear bundle. Brown (1993), Benson and Brown (1996) and Winter, Robertson and

Cole (1989) found that the medial and lateral olivocochlear fiber systems give off branches to the

inferior vestibular nucleus and the lateral vestibular nucleus respectively, apart from those given

to the cochlear nucleus in the mouse and guinea pig. This suggests that these few olivocochlear

fibers might progress further to vestibulospinal tract to stimulate SCM muscle via MVST.

Thus from the above discussion it is evident that there could be three possible pathways

which help in eliciting later peaks of VEMP in individuals with normal hearing sensitivity as

well as in individuals with profound hearing loss. The possible first and third pathway are more

applicable for generation of later peaks of VEMP in individuals with normal hearing sensitivity

whereas second possible pathway might explain the generation of later peaks of VEMP in

individuals with profound hearing loss. So these two mechanisms for generation of later peaks of

VEMP for two different groups might have resulted in lesser and more percentage of presence of

later peaks of VEMP in individuals with normal hearing sensitivity or individuals with profound

hearing loss. Thus, this presence of later peaks of VEMP can give some information of integrity

of cochlear nerve which in turn might help in selecting candidates for cochlear implants. The

proposed possible second pathway might encourage considering acoustic stimulation of the

saccule as an alternative to the cochlear implant.

Pathways for N3 potential:

To understand the possible pathway for N3 potential, later peaks of VEMP and N3

potential were recorded from individuals with profound hearing loss. Results revealed 46.7% of

the population had similar results suggesting that there could be similar pathway for later peaks


75

of VEMP and N3 potential, whereas 53% showed the disagreement between the results

suggesting that there could be two different sites for generation of N3 potential. Thus there could

also be two different sites of origin for N3 potential, one could be vestibular nucleus and other

could be the cochlear nucleus.

The possible site for generation of N3 potential suggested in literature is vestibular

nucleus. Mason (1996) reported a short latency negative component during ABR recordings in

child candidates for cochlear implant suggesting it to be of vestibular origin hence the relation

between sound and the vestibular system is undoubtedly believed. Studies from Elidan and

Honrubia (1987) and Cazals et al., (1987) suggested origin of N3 potential could be the

vestibular nerve and vestibular nuclei. Nong, Kyuna, Owa and Noda (2002) and Ochi and Ohashi

(2001) suggested that N3 potential might be of vestibular origin as is VEMP. Thus, the high level

of acoustic stimulation to the cochlea stimulates the saccule. This excitation of saccular cells in

the saccule then sends the information to the vestibular nucleus via inferior vestibular nerve and

resulted in low amplitude negative potential at around 3 msec. In the process of exploring the

possible pathway for later peaks of VEMP it was observed that a few fibers of the

vestibulospinal tract progress to the dorsal cochlear nucleus (Bukoswka, 2002). This suggests

that negative peak at 3 msec might be of the cochlear nucleus origin also.

The second possible route could be thus explained from the fact that few saccular fibers

enter the cochlear nucleus while progressing towards vestibular nucleus (Kevetter & Perachio,

1989). The intense stimulation to the cochlea stimulates the saccule. Stimulation to the sensory

cells of saccule in turn sends the information to the dorsal cochlear nucleus which might result in

generation of low amplitude negative peak at around 3 msec. The above discussion suggests that

there could be three different pathways for the generation of the later peaks of VEMP and two

possible pathways for generation of N3 potential.

Conclusion

It can be concluded that later peaks of VEMP can be recorded at higher percentage in

profound hearing loss individuals compared to normals. There lies relationship between later

peaks of VEMP and N3 potential as 46.7% of the population showed similar results. Thus there

might be possibility of multiple pathways for later peaks of VEMP as well as N3 potential. For

later peaks of VEMP one pathway might be from cochlea to the Vestibulo-cochlear anastomosis

further progressing to the vestibular nuclei ending at SCM muscle and second could be via

cochlear nucleus to the vestibular nucleus to the SCM muscle. There could also be a third

pathway from cochlea to the medial olivocochlear bundle to the vestibular nucleus descending to

the SCM muscle.

For N3 potential there could be two possible sites of origins. First as Vestibular nucleus

and second might be the cochlear nucleus by stimulating saccule using acoustic stimulation.

Thus this communication between the two systems might have lot of implications in field of

Audiology.


76

Implications of the study:

The study has implication in knowing the pathophysiology of hearing loss in profound

hearing loss.

Non-invasively the condition of the vestibular system (especially the saccule and inferior

vestibular nerve and medial and lateral vestibular nuclei) can be assessed as the later peaks of

VEMP and N3 potentials can only be obtained when saccule is intact and can serve as 2

different tests to check saccular system.

Presence of later peaks of VEMP in profound hearing loss might suggest about the residual

function of cochlea/cochlear nerve in turn helping to decide on candidacy for cochlear

implant.

On the basis of all possible pathways it is evident that there might be a possibility for a

totally deaf person to process acoustic stimulation via a saccular implant.

Limitations of the study:

All the possible pathways proposed have been based on the electrophysiological results. It

would have been better if the results were correlated with other direct methods like injecting

wheat germ agglutinin-horseradish peroxidase (WGA-HRP).

Multiple pathway for each potential limits to find out exact lesion when they are absent,

leading to lack of diagnostic purpose.

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Brown, M. C. (1993). Fiber pathways and branching patterns of biocytin-labeled olivocochlear

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Bukowska, D. (2002). Morphological Evidence for the Secondary Vestibular Afferent

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78

Acoustic Analysis of the Speech Processed Through Three Amplification

Strategies and Their Effect on Speech Recognition Scores of Individual with

Severe Hearing Impairment

Gunjan Chand, Vijayalakshmi Basavaraj & Ajish Abraham

Abstract

Individuals with severe hearing impairment exhibit reduced frequency resolution and

temporal discrimination. Therefore the requirements of amplification for this group of

population will be different from those with lesser degree of hearing loss. The aim of the present

study was to investigate acoustic changes to the speech signal [in terms of Consonant Vowel

Ratio (CVR) and Envelope Difference Index (EDI)] that occurred with different amplification

strategies and to examine the relationship between such changes and speech perception in

individuals with severe sensorineural impairment. A total of 10 subjects having moderately

severe to severe hearing loss participated in the study. Speech Recognition Scores were

calculated for CV nonsense syllable list at input level of 65 and 80 dBSPL for the three

amplification strategies viz Peak Clipping, Compression Limiting, and Wide Dynamic Range

Compression. Consonant Vowel Ratio was calculated for the unprocessed and processed stimuli

for 5 subjects and Correlation Index for one subject at input level of 65 and 80 dBSPL for all the

three strategies using Matlab software. The scores were better with Compression Limiting

compared to Wide Dynamic Range Compression (WDRC) at both 65 and 80 dBSPL. The CVR

values for the processed stimuli with vowel environment /u/ were higher for the Compression

Limiting strategy as compared to WDRC and at 65 and 80 dBSPL for /a/ and /i/ at 80 dBSPL.

The EDI value was greater at 65 dBSPL and as the level increased to 80 dBSPL there was a

decrease in the EDI value for all the three strategies. The results of the present study indicate a

relationship between acoustic changes to the hearing aid processed speech signal and speech

perception performance of severely hearing impaired individuals.

Key words: Peak Clipping, Compression Limiting, Wide Dynamic Range Compression,

Consonant Vowel Ratio, Envelope Difference Index.

Introduction

Sensorineural hearing loss is often associated with loudness recruitment, an abnormally

rapid growth of loudness level with increasing sound level (Moore, 2004). Recruitment could be

due to reduced compressive nonlinearity on the basilar membrane produced by loss of outer hair

cell function (Moore, 1998). The effect of recruitment is represented on the audiogram by the

reduced range between hearing thresholds and uncomfortable loudness levels. In some patients

with large losses, and thus small dynamic range, even the dynamics of speech signal itself causes

Director, All Idia Institute of Speech and Hearing, Mysore, India [email protected] Reader in Electronics, All Idia Institute of Speech and Hearing, Mysore, India


79

problem, amplifying the weak parts of the speech to audible level that causes the strong parts to

be uncomfortably loud.

The feature of Multichannel wide dynamic range compression gives more gain for weak

sounds than for intense sounds. WDRC compresses most of the speech spectrum into the residual

range giving increased audibility and comfort and making loudness perception more similar to

normal (Villchur, 1973). There have been various studies reported in literature that compared

WDRC with Linear amplification and found greatest benefits for WDRC for low level speech in

quiet and conversational level speech in quiet (Souza 2002) and some studies have even shown

small benefits for speech in background noises (Moore, Peters & Stone 1999). However, most of

these studies have dealt with listeners with mild to moderate hearing loss.

The audiological profile differs for different degrees of hearing loss and hence the choice

of amplification also varies. Individuals with severe hearing loss are characterized by

suprathreshold processing deficits primarily by dramatically reduced frequency selectivity

(Faulkner, Rosen & Moore 1990) and in some circumstances by reduced temporal discrimination

(Lamore, Verwiej & Brocaar 1990). It has long been accepted that listeners with a severe loss

require different linear amplification characteristics than listeners with a mild to moderate loss

(Byrne, 1978; Byrne et al., 1990; Schwartz et al., 1988; Van Tasell, 1993). Because of their

broader auditory filters (Faulkner et al., 1990), listeners with a severe-to profound loss may not

be able to take full advantage of spectral information (eg, Erber, 1972) and must rely to a greater

extent on temporal cues which are altered by WDRC amplification (Moore 1996; Van Tasell et

al., 1987). For WDRC amplification one effect is alteration of the natural time-intensity

variations of the speech signal. For listeners with a mild-to-moderate loss who presumably

depend to a greater extent on spectral cues, these changes in time-intensity variations do not

significantly offset the benefits of improved speech audibility (Souza & Turner, 1996, 1998 and

1999).

Souza and Jenstad (2005) attempted to compare speech recognition scores across

different amplification strategies for listeners with severe hearing loss and found that the benefits

of fast acting WDRC relative to more linear amplification may be reduced in listeners with

severe loss. In contrast, Moore and Marriage (2005) studied the effect of three amplification

strategies on speech perception by children with severe and profound hearing loss and found that

speech scores on close set testing for the profound group showed significant benefit for WDRC

over the other two algorithms. The contradictory results could probably be because the latter

study was done on children with congenital hearing loss in whom the dynamic range is reduced

as seen in adults with sensorineural hearing loss.

Review of hearing aids for hearing impairment has shown that signal processing

techniques that take the acoustic- phonetic structure of speech into account promise to be more

effective in improving intelligibility than non phonetically -based methods of signal processing,

provided the relevant speech features are extracted reliably. A form of signal processing which is

phonetically based and which holds some promise for improving intelligibility is that of


80

adjusting the ratio of consonant intensity to vowel intensity (C-V ratio). So the consonant vowel

ratio appears promising as a good measure for selection of suitable strategy for an individual.

Acoustic analysis of single channel syllabic compression and linear amplification has revealed

that compression may result in changes in the intensity relationships between parts of the speech

signal (Hickson & Byrne, 1995). It is expected that increase in the CVR could be expected to

improve consonant perception for people with hearing impairment. Even research in linguistics

with normal hearing subjects reveal that CVR itself is an important cue for perception of certain

sounds. Thus calculating the Consonant Vowel ratio of the speech signal after signal processing

through a hearing aid might help in predicting the performance with that hearing aid. Hickson

and Thyer (1999) reported that it is possible to predict speech perception performance with

compression by examining the acoustic characteristics of the processeed speech signal.

The aim of the present study was to investigate the acoustic changes to the speech signal

(interms of Consonant Vowel Ratio and Envelope Difference Index) that occurred with different

amplification strategies and to examine the relationship between such changes and speech

perception in individuals with severe sensorineural impairment.

Objectives:

1) To study the effects of different amplification strategies on speech recognition scores of

severely Hearing Impaired listeners, 2) To objectively measure the acoustic effects of different

amplification strategies on amplified speech ( by calculating the consonant vowel ratio and

Envelope difference index) and 3) To evaluate the relation between acoustic changes and speech

recognition.

Method

Subjects: Ten (5 males and 5 females) hearing aid users between 20-55 years of age

participated in the study. All subjects had bilateral moderately severe to severe sensorineural

hearing loss (65-90 dBHL) with normal middle ear functioning.

Stimuli: CV items word list containing nonsense monosyllabic words were recorded with a

unidirectional microphone fixed at a distance of 6 inches from the speaker. The recording was

done by a native Kannada speaker seated in a sound treated room. The CV word list consisted of

16 consonants paired with three different vowels /a/, /i/ and /u/ such that most of the speech

frequencies are covered. The word list consisted of 48 CV items shown in Table 1. The stimulus

was recorded at the sampling rate of 44.1 KHz and 16 bit resolution and stored onto the

computer memory. An inter-stimulus interval of 3 secs was introduced between stimuli using

Wave pad Software.

The Speech stimuli and 1 KHz tone were delivered from the same loudspeaker at a

distance of 1 meter from the clients head. Level in dBA was set using the calibration track on the

computer output with the sound level meter (Larsen & Davis) placed in the position of the clients

head without the client present.


81

Table 1- Consonants, Vowels and combination of CV stimuli used in the study

Vowels

Stop Nasal Affricate Fricative Liquid Glide

p b T d k g m n t∫ dz s ∫ h r l v

a pa ba Ta da ka ga ma na t∫a dza sa ∫a ha ra la va

i pi bi Ti di ki gi mi ni t∫i dzi si ∫i hi ri li vi

u pu bu Tu du ku gu mu nu t∫u dzu su ∫u hu ru lu vu

Procedure

[A] Experiment-I: To measure the effect of different amplification strategies on speech

recognition scores:

A routine audiological evaluation that included pure tone audiometry using Carhart-

Jerger Modified Hughson-Westlake (1959) procedure using a calibrated (ISO-389, 1994) dual

channel diagnostic audiometer (MADSEN OB922) with TDH 39 headphone was done. Speech

recognition scores and uncomfortable loudness level for speech was measured. Immitance

measurements including tympanogram and acoustic reflex threshold were carried out using GSI-

Tympstar immitance audiometer to rule out any middle ear pathology. The test was carried out in

an acoustically treated room with noise level within the permissible limits (ANSI S3.1-1991

cited, Wilber 1994). After audiological evaluation subjects were fitted with Phonak Supero 412

Digital BTE Hearing aid having the option of different signal processing strategies: Wide

Dynamic Range Compression, Peak clipping and Compression limiting. The hearing aid was

programmed for all the three signal processing strategies using NAL-NL1 (Dillon et al., 1998)

prescriptive formula using the NOAH Link Compass Version 4 programming software. CV

items were presented from the computer sound card attached to the two channel diagnostic

audiometer. The stimuli were presented via the loudspeaker at the distance of 1 m from the client

at the level of 65 and 80 dBSPL. The responses of the client were noted and scored.

[B] Experiment II: To measure the effect of different amplification strategies on speech

acoustics:

The acoustic measures used in the study were Consonant Vowel Ratio (CVR) and

Envelope Difference Index (EDI) that quantifies the effect of amplification strategies on the

temporal envelope of speech.

1) CVR calculation: The CV items were presented at the level of 65 and 80 dBSPL into an

anechoic chamber through a PC soundcard. A microphone connected to the sound level meter

was placed in the anechoic chamber to record the input stimuli. The stimuli picked up by the

microphone was routed through the SLM and stored on to the computer memory. Using the same

procedure all the CV items were recorded at 65 and 80 dBSPL. In the next step the programmed

hearing aid for each of the different conditions was kept in the anechoic chamber with the

receiver output coupled to a 2cc coupler. The stimuli presented at 65 and 80 dBSPL in the

anechoic chamber were picked up by the hearing aid microphone and the output of hearing aid is


82

picked up by the microphone of SLM and stored onto the computer memory. The CVR was

calculated using an algorithm in Matlab. From the acquired waveforms for the processed and

unprocessed stimuli the consonant and vowel amplitudes are separated out through high pass and

low pass Butterworth filter respectively.

2) Envelope Difference Index: This quantifies temporal changes caused by amplification and a

measure is used for comparing the temporal contrasts of the two acoustic signals called EDI.

Similar procedure was followed for recording the sound as for CVR calculation. The input

waveform of the speech signal the waveform of the amplified signal after passing through the

hearing aid was acquired and the absolute value of the waveforms were taken. The waveforms

were scaled to a mean value of 1. Both the scaled waveforms were correlated using the cross

correlation technique. The CI value was calculated using the formula:

NCI = (∑ ISAMPLE1n – SAMPLE2n1) / 2N

n=1

The procedure was repeated using each of the three amplification strategies.

Results

[A] Experiment-I: The speech recognition scores obtained for 10 subjects were analyzed to

study the effect of amplification strategies and levels. SPSS, Statistical Package for Social

Sciences (version 10) for windows was used to analyze the data. The following parameters were

analyzed.

1) Effect of strategy on Speech recognition Scores: Table 2 shows the overall mean

Speech recognition scores, Standard deviation for different amplification strategies at 65

and 80 dBSPL. The mean scores were better for the Peak clipping (PC) at 65 dBSPL and

for Compression Limiting (CL) strategy at 80 dBSPL.

Table 2- Mean and SD of speech recognition scores across conditions

Level dBspl Strategies Mean SD

65

Compression Limiting 23.8 2.49

Peak Clipping 24.0 3.83

Wide Dynamic Range Compression 21.6 2.72

80




a) At 65 dBSPL input: One-way repeated measure ANOVA was performed for comparison

across strategies within 65 dBSPL. The effect of amplification strategy was significant, F (2, 18)

= 3.661; p < 0.05. Since there was a significant difference across strategies, pair-wise differences

among them was tested with Bonferroni‟s multiple comparison. There was a significant


83

difference between WDRC and CL at 0.05 level of significance. The mean scores were better for

Compression Limiting than WDRC. The remaining pairs were not significant at 0.05 level.

Strategy

CLPCWDRC

Mea

n SR

S

36

34

32

30

28

26

24

22

20

18

16

14

12

10

Level

65 SPL

80 SPL

Graph 1: Mean Percentage Speech recognition scores across strategies

b) At 80 dBSPL input: One-way repeated measure ANOVA was performed for comparison

across strategy for 80 dBSPL input. The effect of amplification strategy was not significant, F (2,

18) = 1.254; p > 0.05.

2) Effect of presentation level on speech recognition Scores

Paired t- test was done for comparison across level within each strategy. The effect of

presentation level was significant for all the strategies, WDRC [t (9) = 4.680, p < 0.05], PC [t (9)

= 6.384, p < 0.05], CL [t (9) = 6.567; p < 0.05]. The scores were higher at 80 dBSPL than at 65

dBSPL.

[B] Experiment II

1. Effect of strategy on consonant vowel ratio: The consonant vowel ratio values were

calculated for 5 subjects. They were analyzed to study the effect of amplification strategy.

a) Peak clipping condition: The CVR values were calculated for the stimuli with vowel

environment /a/, /i/, /u/. Table 3 shows the mean CVR values and Standard Deviation of the

input (unprocessed) stimuli and the output (processed) stimuli in 3 different vowel environments

for 5 subjects.

Paired t test was done to compare the CVR values of the unprocessed and processed

stimuli.

i) Stimuli with vowel environment /a/: There was significant difference between the

CVR values of the unprocessed and processed stimuli at 65 dBSPL [t (15) = 3.451,

p<0.01] and 80 dBSPL [t (15) =4.351, p<0.01]. The CVR values were higher for the

processed stimuli as compared to the unprocessed stimuli both for 65 and 80 dBSPL


84

Table 3: Mean and SD of CVR values for the processed and unprocessed stimuli

Stimuli Mean SD

/a/ 65 Input 0.68 0.14

Output 0.80 0.04

/a/ 80 Input 0.60 0.17

Output 0.77 0.04

/i/ 65 Input 0.39 0.22

Output 0.37 0.10

/i/ 80 Input 0.21 0.18

Output 0.35 0.09

/u/ 65 Input 0.66 0.23

Output 0.67 0.08

/u/ 80 Input 0.58 0.19

Output 0.69 0.08

ii) Stimuli with vowel environment /i/: There was no significant difference between

the CVR values of the unprocessed and processed stimuli at 65 dBSPL [t (15)= 0.736,

p>0.01] whereas difference was seen at 80 dBSPL input [t (15) = 2.899, p<0.01]. The

CVR was enhanced significantly after processing at 80 but not at 65 dBSPL.

iii) Stimuli with vowel environment /u/: There was no significant difference between

the CVR values of the unprocessed and processed stimuli at 65 dBSPL [t (15)= 0.259,

p>0.01] whereas difference was seen at 80 dBSPL input [t (15) = 2.940, p<0.01]. The

CVR was enhanced significantly after processing at 80 dBSPL but not at 65 dBSPL.

b) Compression Limiting: The CVR values were calculated for stimuli with vowel

environment /a/, /i/, /u/. Table 4 shows the mean CVR values and SD of the input

unprocessed stimuli and the output processed stimuli in 3 different vowel environments.

Table 4: Mean CVR values and Standard Deviation for unprocessed and processed stimuli

Stimuli Input/Output Mean SD

/a/ 65 Input 0.68 0.14

Output 0.79 0.04

/a/ 80 Input 0.60 0.17

Output 0.80 0.02

/i/ 65 Input 0.39 0.22

Output 0.41 0.11

/i/ 80 Input 0.20 0.18

Output 0.40 0.08

/u/ 65 Input 0.66 0.23

Output 0.75 0.07

/u/ 80 Input 0.58 0.19

Output 0.71 0.05


85

Paired t test was done to compare the CVR values of the unprocessed input and processed

output stimuli.

i) Stimuli with vowel environment /a/: There was significant difference between the CVR

values of the unprocessed and processed stimuli at 65 dBSPL [t (15) = 2.840, p<0.01] and 80

dBSPL [t (15) =5.035, p<0.01].

ii) Stimuli with vowel environment /i/: There was no significant difference between the

CVR values of the unprocessed and processed stimuli at 65 dBSPL [t (15) = 0.194, p>0.01]

whereas difference was seen at 80 dBSPL input [t (15) = 4.454, p<0.01].

iii) Stimuli with vowel environment /u/: There was no significant difference between the



c) Wide dynamic range compression: The CVR values were calculated for the stimuli with

vowel environment /a/, /i/ and /u/ divided into 6 consonants groups (stops, nasals, affricates,

fricatives, liquids and glides respectively). Table 5 shows the mean CVR values and Standard

Deviation of the input unprocessed stimuli and the output processed stimuli in 3 different vowel

environments.

Table 5: Mean CVR values and Standard Deviation for unprocessed and processed stimuli

Stimuli Input/Output Mean SD

/a/ 65 Input 0.68 0.14

Output 0.70 0.50

/a/ 80 Input 0.60 0.17

Output 0.74 0.05

/i/ 65 Input 0.40 0.22

Output 0.49 0.10

/i/ 80 Input 0.21 0.18

Output 0.35 0.08

/u/ 65 Input 0.66 0.23

Output 0.56 0.06

/u/ 80 Input 0.58 0.19

Output 0.66 0.07

Paired t test was done to compare the CVR values of the unprocessed input and processed

output stimuli.

i) Stimuli with vowel environment /a/: There was no significant difference between the


whereas there was significant difference at 80 dBSPL [t (15) =3.152, p<0.01].


86

ii) Stimuli with vowel environment /i/: There was no significant difference between the



iii) Stimuli with vowel environment /u/: There was no significant difference between the

CVR values of the unprocessed and processed stimuli at 65 dBSPL [t (15) = 1.488, p>0.01] at

80 dBSPL input [t (15) = 1.790, p>0.01].

2) Comparison of CVR values across different amplification strategies

i) Stimuli with vowel environment /a/

a) At 65 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli for all

the 3 conditions are shown in Table 6. The mean CVR values were higher for peak clipping.

Table 6: Mean CVR values across strategies for stimuli with vowel /a/ at 65 dBSPL

One-way repeated measure ANOVA was done to see the effect of amplification

condition. There was a significant effect of amplification condition on the CVR values [F (2, 30)

= 4.946, p< 0.05]. Since there was a significant difference across strategies, pair-wise differences

among them was tested with Bonferroni‟s multiple comparison. There was significant difference

between Peak Clipping and WDRC, WDRC and Compression Limiting at 0.05 level of

significance. There was no significant difference between Peak Clipping and Compression

Limiting at 0.05 level.

b) At 80 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli for all

the 3 conditions are shown in Table 7. The mean CVR values were higher for compression

limiting.

Table 7: Mean CVR values across strategies for stimuli with vowel /a/ at 80 dBSPL

Strategies Mean SD





condition. There was a significant effect of amplification condition on the CVR values. [F (2, 30)

= 10.659, p< .05]. Since there was a significant difference across strategies, pair-wise differences


between Peak Clipping and Compression Limiting, WDRC and Compression Limiting at 0.05

level of significance. There was no significant difference between Peak Clipping and WDRC.

Strategies Mean SD





87

ii) Stimuli with vowel environment /i/

a) At 65 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli

for all the 3 conditions are shown in Table 8. The mean CVR values were higher for

Wide Dynamic range Compression.

Table 8: Mean CVR values across strategies for stimuli with vowel /i/ at 65 dBSPL

Strategies Mean SD






=12.961, p< 0.05]. Since there was a significant difference across strategies, pair-wise

differences among them was tested with Bonferroni‟s multiple comparison. There was

significant difference between Peak Clipping and WDRC, WDRC and Compression Limiting at

0.05 level of significance. There was no significant difference between Peak Clipping and

Compression Limiting.

b) At 80 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli

for all the 3 conditions are shown in Table 9. The mean CVR values were higher for

compression limiting.

Table 9: Mean CVR values across strategies for stimuli with vowel /i/ at 80 dBSPL

Strategies Mean SD








between Peak Clipping and Compression Limiting, WDRC and Compression Limiting at 0.05

level of significance. There was no significant difference between Peak Clipping and WDRC.

iii) Stimuli with vowel environment /u/

a) At 65 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli

for all the 3 conditions are shown in Table 10. The mean CVR scores were higher for



88

Table 10: Mean CVR values across strategies for stimuli with vowel /u/ at 65 dBSPL

Strategies Mean SD






= 42.301, p<0.05]. Since there was a significant difference across strategies pair-wise differences


between Peak Clipping and Compression Limiting, WDRC and Compression Limiting, Peak

Clipping and WDRC at 0.05 level of significance.

b) At 80 dBSPL: The mean CVR values and Standard Deviation for the processed stimuli

for all the 3 conditions are shown in Table 11. The mean CVR were higher for


Table 11: Mean CVR values across strategies for stimuli with vowel /u/ at 80 dBSPL

Strategies Mean SD








between Compression Limiting and WDRC at 0.05 level significance. There was no significant

difference found between Peak Clipping and WDRC and Compression Limiting and Peak

Clipping.

Input and Strategies

Strategy IIIStrategy IIStrategy IInput

95%

CI f

or C

VR V

alue

s at

65

dB

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.1

0.0

Vowels

/a/

/i /

/u/

Graph 2: Error graph showing 95% confidence interval for Consonant vowel ratio at 65 dBSPL for input and output

processed stimuli across strategies.


89

Strategy I- peak clipping, strategy II- compression limiting, strategy III- wide dynamic range

compression

Input and Strategies

Strategy IIIStrategy IIStrategy IInput

95%

CI f

or C

VR V

alue

s at

80

dB

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.1

0.0

Vowels

/a/

/i /

/u/

Graph 3: Error graph showing 95% confidence interval for Consonant vowel ratio at 80 dBSPL

for input and output processed stimuli across strategies. Strategy I- peak clipping, strategy II-

compression limiting, strategy III- wide dynamic range compression.

The range of CVR values was greater for the input stimuli as compared to the output

stimuli at 65 and 80 dBSPL. The CVR values were higher for the stimuli with /a/ and /u/ vowel

environment than for /i/ both for the input and output stimuli as seen in the graph 2 and 3.

2) Effect of strategies on Envelope Difference Index: Table 12 shows the mean Correlation

index values and standard deviation for the stimuli with vowel environment /a/, /i/, /u/ at input 65

and 80 dBSPL for one subject across three strategies. The EDI values were highest for Peak

clipping and lowest for compression limiting at 65 dBSPL whereas at 80 dBSPL it was just the

opposite, highest for WDRC and lowest for Peak Clipping.

Table 12: Mean Correlation index values and standard deviation for the stimuli with Vowel

environment /a/, /i/, /u/ at input 65 and 80 dBSPL

stimuli

strategies

Peak Clipping Compression Limiting Wide Dynamic Range Compression

Mean SD Mean SD Mean SD

/a/ 65 0.29 0.17 0.22 0.18 0.12 0.09

/a/ 80 0.04 0.02 0.74 0.07 0.11 0.10

/i/ 65/ 0.23 0.13 0.20 0.14 0.19 0.15

/i/ 80 0.05 0.05 0.08 0.13 0.12 0.14

/u/ 65 0.13 0.10 0.09 0.06 0.06 0.06

/u/ 80 0.02 0.06 0.05 0.07 0.14 0.15

Discussion

1. Speech recognition scores: Results of the study demonstrated significant difference in speech

recognition scores across strategies at 65 dBSPL but no significant difference between strategies

at 80 dBSPL. The scores were better with Compression Limiting at 65 and 80 dBSPL compared

to WDRC. The study is in agreement with previous study by Souza and Jenstad (2005). Even


90

Hickson and Thyer (2003) found that at higher input levels there was no difference between

linear and compression amplification. We know that variation in amplitude over time provides

critical speech information. Some authors have suggested that severely hearing impaired listeners

depend more heavily on these cues because their broadened auditory filters prevent full access to

spectral detail. In this study data was collected on specific groups of stimuli from a small number

of subjects. To assess the efficacy of the approach it would be desirable to obtain similar

measures from a large number of subjects across a relatively small number of phonetic contrasts.

2. Consonant vowel ratio: The results of the study showed that the Consonant vowel ratio was

better for Compression limiting condition compared to Wide dynamic range compression for the

stimuli with vowel environment /a/ and /i/ at 80 dBSPL and /u/ at 65 and 80 dBSPL. One of the

reasons attributed is that the benefits of recruitment compensation may be nullified in effect by

temporal distortions from the compressor attack and recovery times and their alterations of the

normal intensity cues of speech. As compression limiting is only active at high signal levels it

may provide better CVR without significantly altering the dynamics of conversational speech

signals compared to the effect of a syllabic compressor as speculated by Walker and Dillon

(1982) and Dreschler (1988). The finding of the study suggests that substantial changes in a

speech signal can occur as a result of signal processing by hearing aids. In addition to simple

changes due to frequency shaping, temporal changes such as loss or reduction in the periodicity

associated with voicing and as obscuring of the boundary between aperiodic consonant noise and

the onset of voicing can occur. In this study marked changes in Consonant vowel ratio occurred

with processing. The magnitude of these changes for a given syllable however appears to be

influenced by many factors including system release time, compression parameters, amplitude

and duration of preceding speech sounds, the time delay between the vowel and consonant and

the amplitude of the unprocessed consonant. As such, the changes in the speech signal observed

after processing may not be easily predicted from traditional electroacoustic measures of hearing

aid performance. There is likely to be a complex interaction between the dynamic characteristics

of hearing aid processing and the dynamic characteristics of the speech signal. The result of the

present study indicate a relationship between acoustic changes to the hearing aid processed

speech signal and speech perception performance of severely hearing impaired individuals. The

consonant vowel ratio was higher for the Compression Limiting compared to WDRC strategy

and also the speech recognition scores were better with Compression Limiting compared to

WDRC. So it is clear that the acoustic analysis of the aided speech signal does provide

indicators about the perceptual measures and thus has clinical applications.

3. Envelope difference index: The EDI value was greater at 65 dBSPL and as the level

increased to 80 dBSPL there was a decrease in the EDI value for all the strategies. The change is

more significant for Peak clipping and Compression limiting and not for Wide dynamic range

compression. Since the results were only for one subject one cannot generalize the results.


91

Conclusion

The study represents a step at resolving the clinical issue of how audiologists may choose

the right amplification strategy while prescribing hearing aids for the severely hearing impaired

individuals. The acoustic analysis is an initial step in describing and quantifying the effects of

amplification strategies on phonemes and thus quantifying the benefits of amplification. In the

present study speech recognition scores were calculated in quiet condition which does not depict

real life situations. So, further study may be done to see the effect of amplification strategies on

speech perception in noise. Since the study had certain time restrictions it was done on a small

group of subjects so the results cannot be generalized. Replicated study on a larger number of

subjects may be carried out to validate the results. Hence, studies on acclimatization effects in

long term use of hearing aids and their effect on speech perception can be carried out. The

present study addressed to only the effect of different amplification strategies on speech

perception and speech acoustics. However, there are other compression parameters such as

compression threshold, attack time/release time and compression bands that affect speech

perception. Further studies need to be done to see the effect of these parameters on speech

perception and speech acoustics.

References

Byrne, D. (1978). Selecting hearing aids for severely deaf children. British Journal of

Audiology, 12, 9-22.

Byrne, D., Parkinson, A. & Newall, P. (1990). Hearing aid gain and frequency response

requirements for the severely/ profoundly hearing impaired. Ear and Hearing, 11, 40-49.

Dreschler, W. A. (1988). Dynamic range reduction by peak clipping or compression and its

effects on phoneme perception in hearing impaired listeners. Scandinavian Audiology,

28, 49-60.

Erber, N. P. (1972). Speech-envelope cues as an acoustic aid to lip reading for profoundly deaf

children. Journal of Acoustical Society of America, 51, 1224-1227.

Faulkner, A., Rosen, S. & Moore, B. C. J. (1990). Residual frequency selectivity in the

profoundly hearing impaired listener. British Journal of Audiology, 24, 381-392.

Hickson, L. & Byrne, D. (1995). Acoustic analysis of speech through a hearing aid: effects of

linear vs compression amplification. Australian Journal of Audiology, 17, 1-13.

Hickson, L. M. H., Thyer, N. & Bates, D. (1999). Acoustic analysis of speech through a hearing

aid: consonant vowel ratio effects with two channel compression amplification. Journal

of the American Academy of Audiology, 10, 549-556.

Hickson, L. & Thyer, N. (2003). Acoustic analysis of speech through a hearing aid: Perceptual

effects of changes with two channel compression. Journal of the American Academy of

Audiology, 14, 414-426.


92

Jenstad, L. M. & Souza, P. E. (2005). Quantifying the effect of compression hearing aid release

time on speech acousitcs and intelligibility. Journal of Speech Language and Hearing

Research, 48, 651-667.

Lamore, P. J. J., Verweij, C. & Brocaar, M. P. (1990). Residual hearing capacity of severely

hearing impaired subjects. Acta Otolaryngolica Supplement, 469, 7-15.

Marriage, J. E., Moore, B. C. J. & Stone, M. A. (2005). Effect of three amplification strategies

on speech recognition by children with severe and profound hearing loss. Ear and

Hearing, 26, 35-47.

Moore, B. C. J. (1996). Perceptual consequences of cochlear hearing loss and their implications

for the design of hearing aids. Ear and Hearing, 17, 133-16.

Moore, B. C. J. & Glasberg, B. R. (1998).Use of loudness model for hearing aid fitting. I. Linear

hearing aids. British Journal of Audiology, 35, 349-374

Moore, B. C. J., Peters, R. W. & Stone, M. A. (1999). Benefits of linear amplification and

multichannel compression for speech comprehension in backgrounds with spectral and

temporal dips. Journal of Acoustical Society of America, 105, 400-410.

Moore, B. C. J. & Stone, M. A. (2004). Side effects of fast dynamic range compression that

affect intelligibility in a competing speech task. Journal of Acoustical Society of America,

116, 2311-2323.

Souza, P. E. (2002). Effects of compression on speech acoustics, intelligibility and sound quality.

Trends in amplification, 6, 131- 165.

Souza, P. E. & Turner, C. W. (1996). Effect of single-channel compression on temporal speech

information. Journal of Speech and Hearing Research, 39, 901-911.

Souza, P. E. & Turner, C. W. (1998). Multichannel compression, temporal cues and audibility.

Journal of Speech Language and Hearing Research, 41, 315-326.

Souza, P. E. & Turner, C. W. (1999). Quantifying the contribution of audibility to recognition of

compression-amplified speech. Ear and Hearing, 20, 12-20. .

Villchur, E. (1973). Signal processing to improve speech intelligibility in perceptive deafness.

Journal of Acoustical Society of America, 53, 1646-1657

Van Tasell, D.J. (1993). Hearing loss, speech and hearing aids. Journal of Speech Hearing

Research, 36, 228-244.

Van Tasell, D. J., Soli, S. D., Kirby, V. M. & Widin, G. P. (1987). Speech waveform envelope

cues for consonant recognition. Journal of Acoustical Society of America, 32, 1152-1160.

Walkner, G. & Dillon, H. (1982). Compression in hearing aids: an analysis, a review and some

recommendations (NAL Report No. 90). Australian Government Publishing Service.


93

Some Aspects of Temporal Processing Deficits in Individual with

Learning Disability

Kishan M & Animesh Barman

Abstract

Individual with learning disability are likely to have auditory temporal processing deficit.

Auditory temporal processing deficits lead to inability to process three main temporal features of

speech sounds such as envelope, periodicity and fine structure cues. Since TMTF signal involves

envelope, periodicity and fine structure, TMTF assessment would help in understanding the

ability of the individual in perceiving the amplitude variation in continuous speech. To address

this issue (a) TMTF function across different frequency modulation rates in individual with

learning disability and individual with normal hearing, (b) age related changes in TMTF

perception at different modulation rates in individual with normal hearing and children with

learning disability, (c) comparison of phoneme recognition scores in the presence of noise

between the normal hearing individual and individual with learning disability and (d) the

correlation between TMTF perception and phoneme recognition scores in the presence of noise

for children with learning disability on 24 individuals with learning disability and 20 normal

hearing children were measured. TMTF threshold was obtained at different modulation

frequency (fm: 4, 16, 32, 64 & 128 Hz). SPIN scores obtained in noise at 0 dB SNR and without

noise in both the groups. TMTF threshold showed higher value for children with learning

disability than normal hearing subjects with a peak sensitivity at 16 Hz and 4 Hz in normal and

individuals with learning disability respectively. SPIN score showed no significant difference

between normal and individuals with learning disability. Results suggest that TMTF is a better

predictor of temporal processing deficit.

Key Words: learning disability, temporal modulation transfer function, speech perception.

Introduction

Learning disability is a disorder in the psychological processes involved in understanding

or using language, spoken or written, which may manifest in an imperfect ability to listen, think,

speak, read, write, spell or do mathematical calculations. The causes of learning disability are

unknown and often poorly defined. Children with learning disability have auditory processing

disorder which has been experimentally investigated by many studies. Whether these auditory

processing deficits are seen only in association with language disorder or as a causal factor is yet

to be explored. A majority of studies in the literature report that a subgroup of children with

learning disability has auditory processing disorder. Tallal et al., (1996) described a deficit in

dyslexics involving processing of brief, rapidly changing auditory stimuli. This basic temporal




94

processing impairment underlies their inability to integrate sensory information that conveys

rapid succession in the central nervous system.

Natural speech is a complex signal which has variation in frequency and amplitude with

respect to time. There are three main temporal features of speech namely envelope, periodicity

and fine structure. A number of investigators demonstrated that nearly perfect consonant

identification and sentence intelligibility could be achieved with speech stimuli processed only

with temporal modulation cues which are as low as 50 Hz. (Shannon, 1992; Drullman et al.,

1994). Since TMTF signal involves envelope, periodicity and fine structure, TMTF assessment

would help us in understanding ability of individual in perceiving the amplitude variation in

continuous speech.

Human auditory system has the capacity to resolve the faster and slower changes in the

amplitude, frequency with respect to time. (Separate „fast‟ and „slow‟ auditory system). Any

defects in the development of these two „fast‟ and „slow‟ auditory system may be related to rapid

processing deficits which is common to specific language impairment or individuals with

language learning disability. Individuals with learning disability specifically dyslexics are

impaired in processing the rapidly varying signals which may affect their speech perception

ability in the presence of noisy situation (Tallal, et al., 1996).

TMTF has undergone an extensive research in various populations. Normal-hearing

listeners‟ sensitivity to sinusoidal amplitude modulation threshold is relatively independent of

modulation frequency upto 50-60 Hz, and decreases progressively at higher modulation

frequencies (Viemester, 1979; Bacon & Viemester (1985). For low modulation frequencies (16

Hz), detection is limited by the amplitude resolution of the auditory system rather than its

temporal resolution. As the modulation frequency increases beyond 16 Hz temporal resolution

starts to have an effect and SAM detection threshold increases.

The severe reduction in sentence intelligibility by degrading the consonant identification

were observed in normal hearing individuals when amplitude envelope is low pass filtered

(Drullman et al., 1994; Zeng et al., 1999). However, unlike other psychophysical studies TMTF

is also affected by developmental changes. The psychophysical function varies with the

developmental changes and is applicable to other psychophysical tests. The obtained data

normally may not be suitable to all the population across the world. So attempt has been made in

the present study to obtain norms for the comparison.

Tallal et al., (1996) and Lorenzi et al, (2000) have used TMTF as tool to assess the

temporal processing ability in individual with learning disability and it was assessed at two-

modulation frequencies 2 Hz and128 Hz. Based on their study they said that dyslexics exhibit

impaired ability to perceive the faster modulation which might be leading to poor speech

perception in noise. They measured the ability to process temporal envelope cues in dyslexic

children by measuring detection of sinusoidal amplitude modulation thresholds (SAM). Each

threshold was measured at slow rates and faster rates at 4 Hz and 128 Hz respectively. Overall

SAM thresholds were higher in dyslexics than in normal at both rates. These findings are


95

consistent with Tallal‟s hypothesis, according to which the speech reading deficits in 35% of

dyslexics may be caused by impaired temporal processing which play an important role in

speech perception.

Zeng, Kong, Michalewski and Starr (2005) studied TMTF at different rates and obtained

different patterns in auditory neuropathy in comparison with normal. There is dearth of

information about TMTF approach applied to the individual with learning disability in Indian

context and it is not checked at different rates. The purpose of the present study were therefore to

perform systematic study using different modulation rates in individuals with learning disability

and to see age related changes in TMTF perception. Hence an attempt was made to see the

temporal processing ability of learning disability at different modulation frequencies.

Poor speech perception in noise by individual with normal hearing and cochlear hearing

loss is mainly attributed to degradation caused by noise in processing the low modulation

frequency of the speech signal (Noordhock et al., 1997). From the literature it can be understood

that poor speech perception may be caused when processing of the temporal modulation in the

speech signal is impaired. It has been reported in the literature that dyslexic and individuals with

language delay have poor perception in presence of noise (Sandeep & Vanaja, 2004). Hence the

present study was conducted to investigate phoneme perception ability of different LD in

presence of noise and correlate with TMTF thresholds.

The present study was taken up with the aim to know the: (a) TMTF function across

different frequency modulation rates in children with learning disability having normal hearing

and children with normal hearing without learning disability. (b) Age related changes in TMTF

perception at different modulation rates in children with normal hearing without learning

disability and children with learning disability having normal hearing. (c) Comparison of

phoneme recognition scores in the presence of noise between the normal hearing and children

with learning disability. (d) The correlation between TMTF perception and phoneme recognition

scores in the presence of noise for children with learning disability.

Method

Subjects consisted of 24 children with learning disability (age ranging from 8 to 15 years)

and 21 subjects with normal hearing (age ranging from 8 to 15 years) who formed the clinical

and control group respectively. All the subjects from both the groups underwent hearing

evaluation to rule out the hearing loss by routine clinical hearing evaluation. Pure tone

audiometry was conducted using modified Hughson-Westlake procedure (Carhart &

Jerger,1959) and the threshold were obtained at octaves frequencies from 250 Hz to 8 KHz

using clinical diagnostic audiometer (OB 922) under TDH 39 head phones.

Speech identification scores were obtained by conducting speech audiometry using clinical

diagnostic audiometer (OB 922) under TDH 39 head phones for each ear independently.

Phonetically balanced words developed by Mayadevi (1978) were presented monaurally at 40


96

dBSL or at most comfortable level and speech recognition score was calculated for 100

percentages.

Normal middle ear function was assesed using GSI-Tympstar immittance audiometer.

Each ear was tested separately by placing an airtight probe tip with 226 Hz probe tone and

responses were taken. Similarly stapedial acoustic reflexes were measured at 4 frequencies (500

1 K, 2 K & 4 KHz).

All the subjects in the clinical group had poor scholastic performance in reading, writing

and calculation. These subjects were assessed by experienced speech-language pathologist and

psychologist by using standardized tests materials. Learning Disability was diagnosed by using

“Early Reading Skills” developed by Rae and Potter in 1981 which assesses the ability in terms

of Alphabet test, Visual and auditory discrimination, Phoneme-Grapheme discrimination,

Structural analysis test and reading skills. Psychologist diagnosed the child to have learning

disability based on general assessment and detailed case history to obtain with reference to

reading, writing, calculation, phoneme-grapheme analysis. All the subjects had undergone APD

tests such as dichotic digit test, dichotic consonant vowel test and also speech in noise test.

Majority of them showed poor scores in the APD tests administered. The selection criteria are as

follows for both groups:

Control group

Subject selection criteria:

1. All the subjects had pure tone thresholds within 15 dBHL

2. Speech identification scores of more than 90% in quite

3. Speech identification scores in noise (0 dB SNR) were better than 80%

4. All of them had „A‟ type tympanogram with presence of acoustic reflexes

5. No history of any other problems such as otological and neurological problems

6. The subjects were native speakers of Kannada and English was the medium of instruction

Clinical group

Subjects selection criteria

1. All the subjects had pure tone thresholds within 15dBHL

2. Speech identification scores was better than 90% in quite condition

3. All of them had „A‟ type tympanogram with reflexes present.

4. They were native speakers of Kannada and English was the medium of instruction

5. All of them were free of retardation, autism, brain damage or any other psycho-physical

dysfunction which was ruled out by experienced psychologist and speech language pathologist

and also by detailed case history taken from the parents and school teachers.

6. All of them were diagnosed to have learning disability by experienced speech language

pathologist and psychologist

The clinical group and control group was further divided into four subgroups based on

their age. Subgroup 1 consisted of 7 normal hearing children without learning disability and 6

children with learning disability in the age range of 8 to 8 year 11 months. Subgroup 2 consisted


97

of 3 normal hearing children without learning disability and 9 children with learning disability of

subjects in the age range of 9 to 9 year 11 months. Subgroup 3 consisted of 8 normal hearing

children without learning disability and 4 individual with learning disability number of subjects

in the age range of 10 years to 10 year 11 months. Subgroup 4 consisted of 3 normal hearing

children without learning disability and 5 children with learning disability in the age range of 11

years to 11.11 months.

The following instruments were used for the experiment:

A computer with “speech editing software” was used to generate the TMTF signal.

A calibrated 2 channel diagnostic audiometer (orbiter 922). To route the TMTF signal to

check for the temporal processing ability and to obtain speech identification scores in

quiet and in noise condition. Speech identification score in noise was obtained at 0dB

SNR

Experiment was conducted in two phases, they were:

Test stimuli

The stimuli consisted of unmodulated and sinusoidally amplitude modulated (SAM)

white noise of 500 ms with a ramp of 10 ms. The modulated signal was derived by multiplying

the white noise by a dc-shifted sine wave. The depth of modulation was controlled by varying

the amplitude of modulating sine wave. The expression given below to generate the modulated

noise;

m (t) = [1+ m (sin2π fm t)] * n (t)

Where m is the modulation depth (0<m<1), fm is the modulation frequency (2, 4, 8, 16,

32, 64, 128, 256, 512 Hz) and n (t) is the white noise. Stimuli were low pass filtered at 20 KHz.

All the stimuli were generated using a 32 bit digital to analog converter at a sampling frequency

of 44.1 KHz.

Procedure adapted to establish TMTF threshold:

Subjects were instructed to discriminate the presence of SAM applied to a white noise

carrier. On each trail a standard and a target stimulus were successively presented in random

order to the listener. The standard consisted of white noise n (t). In the target a white noise

carrier was sinusoidally amplitude modulated at a given modulation frequency.

SAM- detection thresholds were obtained using an adaptive two-interval, two-alternative

forced-choice (2I, 2AFC) procedure that estimates the modulation depth „m‟. During one of the

two 500 ms observation intervals continous wideband noise was sinusoidally modulated. The

observer was to discriminate amplitude modulated noise and unmodulated noise. The step size

and threshold were based on the modulation depths in decibels (Am=20 log m). The amplitude of

the modulation was varied according to the following role: „Am‟ decreased 3 dB following a

correct response and „Am‟ increased 3 dB following an incorrect response to obtain the

threshold. The lowest „Am‟ at which modulation is detected was considered as threshold. The


98

lowest threshold that can be measured is 0 dB which corresponds to modulation depth of 1

(100% modulated noise).

The testing was conducted in sound treated room where noise level was within

permissible limits (ANSI-1996). All the stimuli were presented at 40 dB SL. The stimuli were

played from a computer, routed through an audiometer (OB-922) and presented through a loud

speaker which was placed 1 meter away from the subjects at an angle of 0 degree azimuth. The

presentation level was changed in all the subjects at least at one modulation frequency and

modulation detection threshold to ensure that subjects were not using loudness judgments.

The second phase of the study included phoneme perception in the presence and absence

of noise. Subjects were instructed to repeat the phoneme which was heard by them. Speech

material was presented live through the orbiter 922 clinical audiometer. Stimuli were presented

at 40 dB SL or at the comfortable level through the headphones.

Open set phoneme recognition paradigm was used in which listener had to listen to each

phoneme tokens and had to say back in a proper order in quiet condition. Further more, same

speech stimulus was presented monaurally in the presence of noise at 0 dB SNR. Order of the

presentation of the test material was randomized between the conditions for the same subjects to

avoid practice effect. Then the correct response obtained was calculated for 100%.


The obtained data was statically analyzed using SPSS (version 15) software and results are

discussed separately using statistical values.

A. Detection threshold of sinusoidal amplitude modulation:

The following graph shows the TMTF threshold obtained in both control and clinical

group along with standard deviations.

Figure1: Mean TMTF thresholds along with standard deviations at different modulation rates for

individual with normal hearing without learning disability and children with learning disability

without hearing loss.

Normal

LD


99

It can be seen in the figure that normal hearing subjects display a typical low-pass

characteristic i.e. hearing is most sensitive to slow modulation signal but becomes less sensitive

as the modulation frequency increases having peak sensitivity at 16 Hz. A similar trend of typical

low-pass characteristic was also displayed in children with learning disability subjects. However,

they showed much broader response pattern and having peak sensitivity at 4 Hz.

Table 1: Post-Hoc test results of different modulation frequencies for children with LD and with

normal hearing

Modulation Frequency

Number of subjects

Subtest

2 1

4.00

16.00

32.00

64.00

128.00

21

21

21

21

21

-10.57

-10.14

-9.57

-7.92

-

-

-

-

-7.92

-5.78

Sig - .146* .338*

* p< 0.01

A repeated measure ANOVA was performed to assess the significant difference in mean

thresholds between two groups at all modulation frequencies. The analysis showed a significant

main effect between groups [F (1,100=7.65, P<0.01]. No significant interaction between groups

and modulation frequencies [p (4,100) =1.18, P<0.01] were observed. The Scheffe‟s Post Hoc

analysis of variance was carried between the groups across the modulation rates. The results

indicate significant difference between TMTF threshold at 128 Hz modulation frequency from 4,

16 and 32 Hz TMTF thresholds. However, no significant difference between 64 Hz and 128 Hz

thresholds for both the groups was observed.

The normal hearing subjects had significantly lower TMTF thresholds. SAM-detection

thresholds were relatively constant up to 16 Hz but reduced gradually beyond 16 Hz as the

modulation frequency increased. Bacon and Viemester, (1985) also observed similar changes in

their study. This may be because the individuals with normal hearing show significantly larger

physiological response to „Am‟ with respect to variation in signal which will be in synchrony of

neural fibers to modulation (McAnally & Stein, 1997). Children with learning disability had

significantly higher thresholds to amplitude modulation depth than did the normal hearing

subjects. The difference in TMTF performance between two groups could be because the

individuals with learning disability show significantly smaller physiological responses to

amplitude modulated signal than those with normal hearing since they require more synchronous

firing of neurons (McAnally & Stein, 1997). As the modulation frequency increases the

amplitude fluctuations become extremely smoothened and the observer thus required greater

amplitude change in order to resolve the fluctuations (Viemester, 1979) resulting in increase in

TMTF threshold in both the groups.

Poor performance by individuals with learning disability is likely to reflect a true defect

in „Am‟ sensitivity rather than their difficulty in performing the task as shown by previous


100

authors (McAnally & Stein, 1997). They did electrophysiological study in which dyslexic

children also had significantly smaller physiological response to „Am‟ than control group

subjects where they concluded that this may be because of loss of synchrony of neural response

to modulation. This resulted in higher sinusoidal amplitude modulation thresholds in individuals

with learning disability.

The TMTF for individuals with learning disability was similar to that previously

described by McAnally & Stein, (1997); Lorenzi et al. (2000). Threshold obtained in this study

was higher at each modulation frequency. This variation in the thresholds may be accounted to

the procedural difference used to elicit the response whether it is an identification (Lorenzi et al.,

2000) rather than discrimination task.

B. Age related changes in TMTF perception in normal hearing subjects and children with

learning disability across the age

It is evident from the table that as the age increases TMTF threshold decreases.

However, there is no significant difference seen in TMTF threshold across the age. This pattern

was observed in both normal hearing and learning disability group.

Table 2: The mean TMTF thresholds at each frequency along with SD for different age group

Rate

Age

Normal Subjects TMTF Learning Disability Subjects TMTF

4 Hz 16 Hz 32 Hz 64 Hz 128 HZ 4 Hz 16 Hz 32 Hz 64 Hz 128 Hz

8 - 8.11

N=7, LD=6

M -17.5 -17.0 -13.28 -12.0 -9.8 -3.5 -3.5 -6.0 -6.5 -3.5

SD 2.07 2.4 1.6 2.4 8.2 6.1 6.1 0 1.2 5.1

9 - 9.11

N=3, LD=9

M -17.0 -15.0 -14.0 -4.0 -9.0 -8.0 -7.6 -7.3 -6.5 -3.6

SD 1.7 3.0 3.4 3.0 8.0 1.5 1.5 1.5 1.2 1.3

10-10.11

N=8, LD=4

M -15.85 -12.85 -11.14 -10.71 -9.42 -8.25 -6.75 -6.0 -4.5 -4.5

SD 2.1 2.7 3.1 2.2 5.6 1.5 1.5 2.4 1.7 1.7

11-11.11

N=3, LD=5

M -13.50 -13.50 -12.00 -10.5 -4.50 -7.80 -7.20 -6.6 -4.82 -3.60

SD 1.7 1.7 1.7 1.6 5.1 1.6 1.6 1.3 1.6 1.3

N- Number of subjects in normal group; LD- Number of subjects in learning disability group

Table 3: Post Hoc test results to see age related changes in TMTF thresholds across modulation

frequencies in normal hearing subjects and individual with learning disability

Age Learning Disability Normal Hearing

N Subjects N Subjects

8.00-8.11

9.00-9.11

10.00-10.11

11.00-11.11

6

9

4

5

-5.400

-6.446

-6.000

-6.000

6

9

4

2

-11.700

-11.866

-14.250

-12.300

Sig 0.537+ 0.160

+

+

Not significant

In the present study psychophysical test TMTF perception was compared using mixed

analysis of variance to see developmental changes in TMTF modulation depth performance.

Analysis showed that there was no significant difference within subgroup of either control or


101

Learning DisabledNormal Hearing

Mea

n S

peec

h Id

entif

icat

ion

scor

es in

noi

se

100.00

80.00

60.00

40.00

20.00

0.00

clinical groups at each frequency. The significant difference is not seen in this study because the

age range selected was higher and temporal processing maturation might have been complete by

12 years of age. However it also depends on what type of temporal processing tasks are involved

(Chermak & Musiek 1997).

Hall and Grose, (1994) felt that time constant across all age group was interpreted as

indicating that the peripheral encoding of the temporal envelope is probably adult like in children

aged 4 years and above based on their test results. However young children appear to be

relatively inefficient in processing the information underlying modulation detection. In this study

similar trend is not seen because of selected age range being much higher. Hence TMTF

maturation might have completed much earlier and reached adult like response.

C. Comparison of speech perception ability in the presence of noise between the normal

hearing subjects and children with learning disability:

The speech perception scores obtained at 0 dB SNR in normal hearing subjects were

better than the scores obtained in individuals with learning disability. There was no significant

difference between SIS scores of left and right ear in both the groups. Hence the scores were

combined to compare the performance between normal hearing subjects and children with

learning disability. Analysis was done using paired sample t-test to know the significance

difference if any between the ears and independent samples t-test between the groups.

Figure 2: Speech identification scores in noise obtained in children with normal hearing and learning disability

Results showed that there was no significant difference in the performance between the

groups in right ear [t=3.07, P<0.01] and left ear [t=3.2, P<0.01]. Similar kind of performance

was also obtained by earlier studies by Ferre and Wilber (1986). They reported that an individual

with learning disability shows poor performance in CAPD tests including speech in noise test.

Lorenzi et al (2000) obtained unprocessed speech signal and speech envelope noise signal

identification and observed that individual with dyslexia exhibit poor performance in processing

the speech envelope noise when compared to normal hearing subjects. However in the present

study few children with learning disability had showed equal performance to that of normal

hearing subjects. This might be because all children with learning disability may not exhibit

auditory processing problem.


102

Speech is a complex signal which has variation in its amplitude and frequency of the

spectrum (temporal envelope). Presence of background noise will mask the variations in

frequency and amplitude of the signal and the signal becomes less redundant to be processed.

Chermak and Musiek (1997) reported that the individuals with normal auditory system will be

able to process selectively to speech spectrum by ignoring the background noise whereas an

individual with auditory processing problem will fail to extract the information from the complex

signal. Thus this might have resulted in poor speech recognition scores in the presence of noise

in learning disability group.

D. Correlation between TMTF perception and phoneme recognition in the presence of

noise obtained from individual with learning disability:

In the present study to see the correlation between SPIN scores and TMTF thresholds

peak sensitivity was calculated for the lowest threshold across modulation frequency which in

turn correlated with SPIN scores in children with learning disability. To obtain correlation

between these two variables Pearson‟s product moment correlation was used to analyze the data.

The analyses showed that there is a significant correlation between these two variables (r = -

0.39, P<0.01). However, a few subjects showed better performance in SPIN scores equal to that

of normal. This may be because speech in noise test is less sensitive and less reliable tool in

assessing auditory processing deficits (Chermak & Musiek (1997). Results obtained in the

current study reveals that TMTF is a sensitive test to assess temporal processing ability than the

speech in noise test, to differentiate processing problem that may be auditory based rather than

linguistic based. However until now there is no study reported regarding correlation between

TMTF and speech perception in the presence of noise.

Conclusion

From the above discussion it can be concluded that learning disability required higher

modulation depth to perceive the modulation than the normal group. The peak sensitivity for

normal hearing children is higher than for children with learning disability. SPIN scores are

likely to be poorer for learning disability than normal group, thus suggesting temporal processing

deficit in learning disability. TMTF could be better test to assess temporal processing than SPIN.

Data obtained in normal hearing group at different modulation rates can be used as a normative

data (as shown in fig 1).

Clinical implication:

1. TMTF is an effective, non invasive, quick and sensitive tool which helps to identify temporal

processing disorder, especially in individuals with learning disabilities.

2. TMTF performance in combination with SPIN scores gives a better idea about whether the

processing problem is linguistic- based or auditory- based problem.

3. TMTF perception indirectly assesses how well an individual can perceive speech

4. Early indication to diagnosis at risk of learning disability

5. Also can be used in rehabilitation


103

References

American National Standards Institute. (1996). “American National Standard Maximum

Permissible Ambient Noise Levels for Audiometric Test Rooms”. ANSI S3.1- (1996).

New York: American National Standards Institute.

Baccon, N. F. & Viemester. (1984). Temporal modulation transfer function in normal hearing

and hearing impaired listeners. British Journal of Audiology, 24, 117-134.

Bacon, S.P. & Viemeister, N.F. (1985). Temporal modulation transfer functions in normal-

hearing and hearing–impaired subjects. Audiology, 24, 117-134.

Carhart, R. & Jerger, J. F. (1959). Preferred method for clinical determination of pure-tone

thresholds. Journal of Speech and Hearing Disorder, 24, 330-345.

Chermak, G.D. & Musiek, F. E. (1997). Central Auditory Processing Disorders: New

perspectives. San Diego: Singular Publishing Group

Drullman, R., Festen, J.M. & Plomp, R. (1994). The effect of temporal envelope smearing on

speech reception. Journal of the Acoustical Society of America, 95, 1053-1064.

Drullman, R., Festen, J.M. & Plomp, R. (1994). Effects of reducing slow temporal modulation

in speech reception. Journal of the Acoustical Society of America, 95, 2670-2680.

Kraus, N., McGee, T. J., Carrel, T.D., Zeeker, S.G, Nicol., T.G. & Koch, D.B. (1996). Auditory

Neurophysiology Responses and Discrimination Deficits in children with learning

problem. Science, 273, 971-973.

Lorenzi, C., Wable, J., Moroni, C., Derobert, C. & Belin, F. C. (2000). Auditory temporal

envelope processing in a patient with left-hemisphere damage. Neurocase, 6, 231-244.

Mayadevi (1978). The development and standardization of a common speech discrimination test

for Indians. Unpublished master dissertation, University of Mysore, Mysore.

McAnally, K.I. & Stein, J. F. (1997). Scalp potentials evoked by amplitude-modulation tones in

dyslexia. Journal of Speech, Language and Hearing Research, 40, 939-945.

Sandeep, M. & Vanaja, C.S. (2004). Auditory long latency responses in children with learning

disability and normal hearing subjects. Unpublished dissertation, submitted to university

of Mysore.

Shannon, R. V. (1992). Temporal modulation transfer function in cochlear implant patients.

Journal of the Acoustical Society of America, 91, 2156-2164.

Tallal, P., Miller, S.T., Bedi, G., Byma, G., Wang, X., Nagarajan, S., Schreiner, C. & Jenkins,

W. (1996). Language Comprehension in Language Learning Impaired Children

Improved with Acoustically Modified Speech Science, 271, 81-84.

Viemester, N. F., (1979). Temporal modulation transfer function based upon modulation

thresholds. Journal of the Acoustical Society of America, 66, 173-178.

Zeng, F. G., Oba, S., Garde, S., Sinnger, Y. & Starr, A. (1999). Temporal and speech processing

deficits in auditory neuropathy. Neuroreport, 10, 3429-3435.

Zeng, F.G., Kong, Y. Y., Michalewski, H.J. & Starr, A. (2005). Perceptual consequences of

disrupted auditory nerve activity. Journal of neurophysiology, 93, 3050-3063.


104

Speech recognition of spectrums with ‘holes’ by children

Manasa Ranjan Panda & Asha Yathiraj

Abstract

The identification of speech having holes in various bands in the spectrum was assessed

in 30 normal hearing children. The speech material that was developed simulated perception

through a twenty–two channel cochlear implant using noise band simulation technique. The

„holes‟ in the spectrum were created by filtering specific frequency bands which corresponded to

the frequency bands of adjacent electrodes in a Nucleus cochlear implant. Responses were

scored in terms of words and phonemes as well as consonants and vowels. It was found that

there were less consonant errors than vowel errors for both word scoring and phoneme scoring.

This error pattern was more with larger „hole‟ size. It was also noticed that younger children in

this study showed significantly poorer performance than older children.

Key words: spectral hole, filter, simulation.

Introduction

It is generally accepted that humans rely on cues that exist across several frequency bands

to understand speech. The question of how listeners use and combine information across several

frequency bands when understanding speech has puzzled researchers for many decades. It can be

recognized even when the spectral information is reduced to three sinusoids that track the

formant transitions over time (Remez, Rubin, Pisoni & Carrell, 1981). A high degree of speech

discrimination and recognition is observed even under conditions of great reduction of spectral

information. (Van Tasell, Greenfield, Logemann & Nelson, 1992; Shannon, Zeng, Wygonski,

Kamath & Ekelid, 1995; Turner, Souza & Forget, 1995).

Understanding how speech is perceived after being processed through a cochlear implant

is a challenge. In cochlear implants a relatively small number of electrodes activate tonotopic

patches of neurons with a portion of the speech signal. Even with these abnormalities in

physiologic process Shannon et al. (1995) found high levels of phoneme, word and sentence

recognition could be achieved by adults with just four bands of information. This observation

indicates how little is understood about recognition of speech under conditions of distorted

spectral information.

Cochlear implantation is based on the idea that there are surviving neurons in the vicinity

where electrodes are placed in the cochlea. The lack of hair cells and/or surviving neurons within

the areas of cochlea essentially creates „hole(s)‟ in the spectrum. The influence of the „holes‟ in




105

the spectrum in speech understanding is not well understood. It is not known whether the spectral

„holes‟ can account for some of the variability in the performance among cochlear implant users

(Kasturi, Loizou, Dorman & Spahr, 2002). Hence, it is of interest to find whether recognition

will be affected with the set of „hole‟ pattern in speech.

Shannon, Galvin and Baskent (2001) assessed the impact of size and location of spectral

„holes‟ in cochlear implantees and normal hearing listeners. Results showed that holes in the low

frequency region are more damaging than holes in the middle or high frequency region on

speech recognition. Vidya, Rima and Yathiraj (2006) evaluated perception of seven lists of

words having different band rejections and one list with no modification on thirty normal hearing

adults. They found that despite information being filtered from the speech signal perception was

not altered. Based on their findings they interpreted that as many as eight adjacent electrodes

could be switched off in a cochlear implant without affecting speech identification. This gives an

insight of how cochlear implant users perceive speech even when specific electrodes are

switched off.

Various research findings contradict each other regarding number of electrodes recquired

for better speech performance. Holmes, Kemker and Mervin (1987) evaluated speech perception

of a patient fitted with a multichannel processor under different electrode conditions. Their study

suggested that by increasing the number of programmed electrodes the subject‟s speech

perception improved. This finding contradicts that obtained by others (Dorman, Loizou &

Rainey 1997; Shannon et al. 1995; Turner, Souza & Forget, 1995). Dorman et al. (1997)

processed vowels, consonants and sentences through software emulations of cochlear implant

signal processors with 2-9 output channels. They found that high levels of speech understanding

could be obtained using signal processors with a small number of channels. Despite many

investigations the basic question of “how many electrodes for speech information” are still to be

answered.

Knowing the relation between the numbers of electrodes activated and speech

recognition is necessary for future designing devices as well as during counselling. Clinically a

number of conditions may necessiate reducing the number of electrodes in a cochlear implant or

not programming the electrodes. The effect of spectral resolution on speech recognition has

received considerable attention in last few years. However, this attention is mainly concentrated

on adults (Dorman et al., 1997; Fu, Zeng, Shannon & Soli., 1998; Holmes et al., 1987; Shannon

et al., 1995, 2001; Vidya et al., 2006). It is theoretically and practically important to understand

whether the limited spectral resolution is a key factor for children also. Eisenberg, Shannon,

Martnez, Wygonski and Boothroyd (2000) reported that young children did not have sufficiently

developed speech pattern recognition. Thus children may require more spectral channels than

adults to obtain similar speech recognition skills. Hence there is a need to study to assess the

effects of spectral „hole(s)‟ in children using cochlear implants.

Besides evaluating the effect of spectral „holes‟ on individuals using cochlear implant it

has also been evaluated on normal hearing individuals using simulated material. This has been a


106

preferred method of study due to the ease with which the research can be conducted. It has also

been found that controlling subject-related variables are a lot easier in a simulated condition.

Thus the present study aims at investigating speech recognition in children using a cochlear

implant simulated condition. Recognition of speech with varying spectral „holes‟ will be studied.

Method

Participants

Thirty children with normal air conduction and bone conduction thresholds in the

frequency range of 250 Hz to 8 KHz and 250 Hz to 4 KHz respectively, participated in the study.

The children were in the age range of 7-10 years. They were native speakers of Kannada and

were able to read and write the language. They had no history of any neurological disorders and

had normal middle ear functioning as measured by tympanometry and acoustic reflexes.

Instrumentation

A Pentium IV computer with Matlab software was used for the development of the

material. A CD burner (Nero 7 Ultra Edition) was used to write the material on a CD. To

evaluate as well as present the test items a calibrated two channel audiometer (Madsen OB 922)

with TDH 39 earphone was used. The middle ear status was determined with measurements from

GSI Tympstar immittance meter. The speech material was played through a Philips CD player.

Material development

The speech identification test material “The Kannada Phonemically Balanced words”

developed by Yathiraj and Vijayalakshmi (2005) was used to simulate speech processed through

a cochlear implant. The test consisted of four lists of bisyllabic words with each list having 25

words. The CD recorded version of the test was used. The below mentioned procedure was used

to simulate speech processed through a twenty-two channel cochlear implant.

The words of each of the original lists were randomized to create eight lists. These speech

signals were band pass filtered into twenty-two frequency bands using 6th

order Butterworth

filters. Crossover and center frequencies were calculated using the following equation relating

the position on the basilar membrane to its characteristic frequency and assuming a basilar

membrane length of 35 mm (Greenwood, 1990, cited in Rosen, Faulkner & Wilkinson, 1999):

Frequency = 165.4 (10 0.06x

-1)

X = 1/0.06 log (Frequency/165+1)

The envelope detection occurred at the output of each filter by full wave rectification and

second order Butterworth low pass filter at 400 Hz. Forward and backward filtering were used to

cancel the phase delays. These envelopes were then multiplied by signal correlated noise. Before

being summed the signal was passed through an output filter similar to the analysis filter (Figure

1). Two conditions were created - “no „hole‟ condition and “dropped” condition. In the dropped

condition seven lists were created in which the output noise bands were simply omitted (band


107

pass filtered with 6th

order Butterworth filter) from the processed signal. The „hole‟ size was

calculated corresponding to each of the dropped condition. The frequency bands of the band stop

filters and „hole‟ sizes are shown in Table 1. These band rejections were created in the

frequencies which corresponded to frequency bands of groups of adjacent electrodes in a

Nucleus cochlear implant. The above procedure was carried out using Matlab software. In the no

„hole‟ condition no band pass filtering was carried out. Prior to each test stimuli a 1 KHz

calibration tone was also recorded. The altered stimuli were recorded on a compact disc (CD).

Figure 1: Block diagram of the processing used for transforming the speech signal

Test Environment

The test was carried out in a two-room audiometric set-up which was acoustically

treated. The noise level was within permissible limits as recommended by ANSI (1991).

Table 1: Band rejection done for specific lists

Procedure

The hearing sensitivity of the participants was assessed using a calibrated two channel

audiometer (Madsen OB 922) with TDH 39 earphone. A GSI Tympstar immittance meter was

used to evaluate the status of the middle ear and to obtain acoustic reflex. Thirty children who

met the subject selection criteria participated in the study.

The developed material was played using a Philips CD player. The output from the player

was routed to the tape input of the two-channel audiometer. Prior to the speech signals being

Lists Frequency bands Hole size

LIST 1 438-813Hz 3.4 mm

LIST 2 938-1313Hz 2.0 mm

LIST 3 1563-2313 Hz 2.6 mm

LIST 4 2688-4063 Hz 2.8 mm

LIST 1 A 4688-6938 Hz 2.8 mm

LIST 2 A 438-1063 Hz 5.1 mm

LIST 3 A 438-1313 Hz 6.4 mm

LIST 4 A No filter -

Full wave

rectifiers Output

filters

Analysis

filters

400 Hz

Low

pass

Speech

input Multipliers

White noise

source

Sum noise

bands


108

presented the recorded 1 KHz calibration tone was played. This was used to adjust the VU meter

deflection to zero. The signal was presented at 40 dB HL. The output from the audiometer was

heard by the participants through circumaural headphone. Half the participants heard the signal

in the right ear and the other half in the left ear. The order in which the lists were presented was

randomized to avoid any list order bias. The participants were instructed to write down the words

they heard.

Scoring

The written responses of the participants were scored in terms of phonemes as well as

words that were correctly identified. For word scoring, each correct response was given a score

of one and a wrong response a score of zero. The maximum possible word score for each list was

25. For phoneme scoring, each correct response was scored as one and wrong as zero. The

maximum possible scores for list 1/1A, 2/2A, 3/3A and 4/4A was 103, 103, 104 and 106

respectively.


Statistical analysis was done using the SPSS software (version, 10.0). Descriptive

statistics and repeated measure ANOVA was carried out on the data obtained from the thirty

children to check significance of difference of speech identification scores across different filter

conditions. This was done across all the filter conditions as well as non-filter condition. Both

word scores and phoneme scores were analyzed for each filter condition.

A) Effect of different band stop filters on speech identification scores

The mean and standard deviation for the word scores and phoneme scores are shown in

Tables 2. This information is provided for all eight lists that were evaluated. Details of the vowel

and phoneme scores are discussed below.

Table 2: Mean and SD for the word and phoneme scores for different filter conditions

Lists Band

Rejections

(Hz)

Word Score Phoneme Score

Mean scores SD of raw scores Mean scores SD of raw

scores

List I 438-813 49.08% (12.27) 5.56 80.30% (82.73) 9.01

List II 938-1313 52.52% (13.13) 6.13 84.36% (86.90) 8.28

List III 1563-2313 56.28% (14.07) 6.02 83.46% (86.80) 10.00

List IV 2688-4063 54.00% (13.50) 7.16 81.00% (85.86) 11.51

List IA 4688-6938 57.48% (14.37) 5.85 85.95% (88.53) 8.53

List IIA 438-1063 58.28% (14.57) 5.67 87.01% (89.63) 7.62

List IIIA 438-1313 52.00% (13.00) 6.56 83.71% (87.06) 9.93

List IVA No Filter 57.20% (14.30) 6.34 85.08% (90.13) 9.03

Note: Maximum word score = 25; Maximum phoneme scores vary from 103 to 106

Values given in bracket refer to the raw score


109

The word scores across filter conditions were relatively low, including the unfiltered

condition. This indicates that the material simulating speech processed through a twenty-two

channel cochlear implant resulted in reduced word scores without and with band stop filters.

This highlights that the simulated material resulted in distortion reducing the overall

intelligibility of the developed material.

A repeated measure ANOVA revealed that there was a significant difference between the

word scores across the different lists [F (7, 203) =3.957, p < .05]. The Bonferroni multiple

comparison tests further indicated that for the word scores there was a significant difference

between List I and List IIIA; List IV and List IVA at the level of 0.05 level of significance.

Surprisingly, though the „hole‟ was larger for List IIIA, the performance was poorer for List I.

Though both the lists were equal in terms of phonemic balance and difficulty the variations in

test items could have led to the difference in performance. The participants may have been able

to utilize coarticulated information to a greater extent in List IIIA than in List I.

A significant difference was also found between List IV and List IVA. List IVA was

without any „hole‟ whereas List IV had a „hole‟ of 2.8 mm. The cutoff frequencies used to create

List IV were in the frequency region of the second format (F2) for several of speech sounds and

F2 is a major cue to differentiate vowels (Carlson, Fant & Grantson, 1975). Hence removal of

F2 information in List IV might have led to a significant difference compared to that of the no

„hole‟ condition. However, no significant differences were found for word scores across all other

lists. Based on this finding it can be inferred that generally the listeners were able to combine the

information across various frequency bands to perceive a “whole” signal.

The phoneme score across filter conditions was found to be significantly different on the

ANOVA test across the eight lists [F (7, 203) = 7.863, p < .05]. This significant difference was

observed between List I and Lists IA, III, IIIA, IV and IVA. In addition List IV significantly

differed from List IVA. The difference in phoneme scores can be attributed to increase in „hole‟

size. The „hole‟ size for List I was larger (3.44 mm) when compared to List IA (2.8 mm), List III

(2.6 mm) and List IV (2.8 mm).

The finding of the present study is in agreement with the findings of Shannon et al.

(2001). They too reported that speech recognition decreased as the „hole‟ size increased in

normal hearing adults. They reported that a 4.5 mm „hole‟ caused the performance to decrease

significantly for consonants and vowel recognition. However, in the present study, it was found

that a „hole‟ size of more than 2.6 mm was able to reduce speech recognition. This difference of

findings in both the studies might be due to test procedure and age of the participants. Shannon et

al. (2001) carried out the experiment on adults in a free field condition while the present study

was carried out on children under head phones. The task in the study by Shannon et al. (2001)

was to identify medial vowels and medial consonants. However, in the present study, consonants

and vowels in the initial, medial and final position had to be identified. This might have also

attributed to difference in findings.


110

Shannon et al. (2001) also found that decrease in speech recognition was larger for apical

„holes‟ than basal „holes‟. In the present study also the „holes‟ representing the apical region of

the cochlea resulted in poorer scores (List I) when compared to the „holes‟ representing the more

basal regions. However, this was not seen for all „holes‟ representing the basal region. No

significant difference was found among other lists. It showed that listeners were able to

effectively combine information from different frequency regions and perceive the speech signal

despite the removal of certain frequency components.

In general, higher phoneme scores were obtained for phonemes in comparison to word

scores. Similar results were also found by Olsen, Van Tasell and Speak (1997) in a group of

normal hearing adults. In their study, phoneme scoring yielded scores that were on the order of

20% higher than scores for whole words heard. Barick (2006) also found a significant difference

in word and phoneme scores. He recommended that word scores be calculated rather than

phoneme scores since this scoring procedure depicts the perceptual problem better. However, he

suggested that if the client was to be referred for auditory listening training the phoneme scoring

procedure should be used.

Phoneme scores as a function of age was evaluated across filter conditions. All the

participants were classified into four age groups, 7-8, 8-9, 9-10 and 10-11 years. The Duncan

post hoc test revealed that the youngest group (7-8 year old) performed significantly poorer than

the older three groups.

The finding regarding the performance of different age groups is similar to that reported

by Eisenberg et al. (2000). They too noted that the youngest group in their study (5-7 year old)

performed significantly poorer than their older children aged 10-12 years on a speech perception

task. They had used age appropriate test material and found it on a variety of age matched tasks.

They reported in their study that the younger children were more variable in their performance

than adults and older children suggesting probable cognitive or task related factors playing a

role.

Thus the findings of the present study substantiate the presence of a developmental trend

in the perception of spectral „holes‟. This indicates that unlike the older children younger

children are unable to carry out an auditory closure activity and guess the material that has been

presented to them.

B) Phoneme errors as a function of different band stop filters

In addition to obtaining word and phoneme scores confusion of vowels and consonants

were observed in each lists. Further, an error analysis was carried out for both the vowels and

consonants to assess the error pattern. The analysis was done for three lists (List I, List III and

List IA). These three lists were analyzed as they represented low (438-813 Hz), mid (1563-2313

Hz) and high (4688-6938 Hz) frequency band-stop filters respectively. Overall less consonantal

errors were noticed than vowel errors (Table 3). Probably due to the larger number of redundant

segmental cues present in consonants the participants were able to guess them despite the


111

presence of „holes‟ in the spectrum. Thus if one cue is missed due to filtering listeners can

perceive the other cues and identify the consonants. Despite vowels being more robust the

number of redundant segmental cues present in them is less.

Vowel Errors

Among the three lists the least errors were observed in List IA, followed by List III and

List I. In List IA, the cutoff frequency was between 4688-6938 Hz whereas the cues for vowel

perception lie between 270 Hz and 2160 Hz (Peterson & Barney, 1954). Thus, in List IA, all the

information for the perception of vowels was preserved. Hence the spectral „hole‟ in it did not

adversely affect the perception of vowel. In contrast the errors were maximum in List I as it

removed the low frequency component in which first formants for all the vowels and second

formants of many vowels lie (Peterson & Barney, 1954).

Further, the error analysis of these three lists revealed that there was confusion between

short and long duration vowels. This was observed across all the three lists. This highlights that

the simulated speech material affected the temporal cues required for the perception of long

versus short vowels, resulting in this confusion. The error analysis for vowels also highlighted

that in List I which contained the low frequency spectral „hole‟, /u/ was confused with /i/ and /o/

was confused with /a/. Elimination of essential formant information probably resulted in this

confusion.

Table 3: Consonants and vowel errors across different filter condition

List Consonant errors (in %) Vowel errors (in %)

List I 40.0 60.0

List II 44.0 56.0

List III 41.1 58.8

List IV 42.1 58.8

List IA 40.6 60.0

List IIA 46.6 53.3

List IIIA 35.3 64.7

List IVA 46.6 53.3

Consonant Errors

The consonantal error analysis was carried out in the same three lists as that done for

vowels. In all the three lists voicing, place of articulation and manner was noticed to be affected.

However, majority of errors were observed for place of articulation followed by manner and

voicing errors. Manner and voicing cues have been found to be primarily temporal cues (Van

Tassel, Soli, Kirby & Widin, 1987) and they require minimal spectral cues to be accurately

perceived (Shannon et al., 1995). In contrast place cues require spectral cues which are affected

by the spectral „holes‟. Similar results were also obtained by Shannon et al. (2001). They too

reported that information received on place of articulation decreased considerably as the „hole‟

size was increased particularly when the „hole‟ was located apically. In the present study


112

maximum errors were obtained in List I which had a „hole‟ located more apically. The „hole‟

size in the List I was 3.4 which was larger than the other two lists. This apical location and larger

size might have lead to more errors in List I. Also the alveolar /d/ was confused with labial /b/

and velar /k/ in List I and in List IA respectively. Generally the major cues for the perception of

place of articulation of stops are the bursts and second format transition (Cooper, Delattre,

Liberman, Borst & Gerstman, 1952). The spectal „holes‟ in the speech material probably

eliminated some of the major cues, causing confusion in the place of articulation perception.

Conclusion

From the findings of the present study it can be concluded that with increase in „hole‟

size there was a deterioration in speech recognition scores. The apical location of „holes‟ or

band-stop filters affected speech perception more than the basal „holes‟ or band-stop filters.

However, not all the basal „holes‟ had the similar adverse affect. The phoneme scores were

higher in comparison to word scores. The error analysis indicated that consonantal perception

was better than vowels for all filter condition. This error pattern was more with larger „hole‟ size.

However, this trend was not followed in all of the lists suggesting that listeners were able to

combine the information from other frequencies to perceive the whole signal. Among vowels

maximum confusion was noticed among short versus long vowels. For consonants more place of

articulation confusion than manner and voicing confusion was observed. It was also noticed that

7-8 year old children showed significantly poorer performance than older children.

The present study will add to the current knowledge-pool of understanding speech pattern

recognition in young cochlear implantees and their perceptual differences in the speech

recognition with adults. Clinically findings of this study may help in predicting speech

perception as a function of the electrodes that are switched on. Information from the study would

be useful in counselling parents of young cochlear implantees or cochlear implantees regarding

the speech sounds that will be affected if specific electrodes would be switched off.

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York: American National Standards Institute (ANSI), 1991.

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University of Mysore, Mysore.

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experiments on the Perception of Synthetic Speech Sounds. Journal of Acoustical Society

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number of channels of stimulation for signal processors using sine-wave and noise-band

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Eisenberg, L., Shannon, R. V., Martnez, A. S., Wygonski, J. & Boothroyd, A. (2000). Speech

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Importance of Long Latency Potential in Pediatric Hearing

Assessment

Niraj Kumar & Animesh Barman*

Abstract

Numerous researchers‟ reports caution clinicians that infants with risk factors have

reversible features of auditory dys-synchrony (AD). It is important for an audiologist to be able

to differentiate such reversible condition or auditory maturational delay (AMD) from non-

reversible AD. It is difficult to identify the exact nature and type of hearing loss in infants and

toddlers with risk factors using routine audiological test battery as they present inconclusive

tests results (ABR, BOA, OAE & Immittance) in a single assessment. So an appropriate test

battery becomes essential in order to differentiate these mimicking conditions. Thus, the study

was taken up with the aim to check the importance of LLR in pediatric hearing assessment,

especially to differentiate AMD from AD and permanent hearing impairment. 55 infants/

toddlers (30 males & 25 females) were taken for the study with age below 2 years at the time of

first evaluation. They were divided into four groups on the basis of ABR and LLR results. The

results revealed that LLR is an important tool in differential diagnosis of different conditions that

are likely to be encountered when dealing with the hearing assessment of pediatric population of

infants/toddler less than 2 years of age. In LLR results large variability was observed across the

subjects. So, it is recommended that the interpretation of LLR wave be cautiously approached

especially with regard to the absolute latency. It is also recommended that rather than looking at

the latency it would be better to look for the presence or absence of LLR for the differential

diagnosis of different conditions.

Introduction

Approximately 10% of newborns are at risk for medical problems and developmental

disability. Most infants at risk are detected either at birth as reflected in low APGAR scores or

during the complete physical examination within few hours of birth.

Different aspects of neurogenesis take place somewhat independently yet simultaneously

and interactively in infants. Degenerative and regressive events involving cell death, retraction of

axonal process and elimination of synapses occur concurrently throughout the development

(Berry, cited in Salamy, Eggermont & Elredge, 1994). Literature on developmental outcomes of

infants has shown that at risk infants display increased susceptibility to a variety of physical and

developmental deficits.

Hearing is critical for normal speech and language development which in turn is vital for

most aspects of normal human development. A significant hearing impairment at birth can




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produce major disruption in language learning (Menyuk, 1977) and produce irreversible deficits

in the development of central auditory pathways (Moore, 1985). Even a mild hearing impairment

has been implicated in delayed development of auditory skills (Quigley, 1978). Early

identification of hearing loss followed by appropriate management minimizes the auditory

deprivation which can interfere with speech and language learning and central nervous system

maturation. So, early identification will waive off a number of problems regarding person‟s

educational, social and economic development that might arise in future.

Hearing loss in children is silent and hidden disability. It is hidden because children,

especially infants and toddlers, cannot tell us about their inability to hear well. However, there

are several ways to identify hearing loss in infants. There are subjective and objective methods to

identify hearing impairment. Such methods usually do not involve the subjects‟ active

involvement. Most commonly used behavioral method is Behavioral Observation Audiometry

(BOA) and the objective methods are Auditory Brain-stem Response (ABR), Oto-Acoustic

Emissions (OAE) and the Immittance audiometry, among which ABR is the most commonly

used tool to identify presence or absence of hearing loss.

Galambos and Galambos (1975) found a drop in latency of the ABR peaks with age in

the premature infants which they attributed to maturational changes. Roberts, Davis, Phon,

Reichet, Sturtevants and Marshall (1982) concluded that ABR failures in the infants in their

study resulted mainly from immaturity. Raj, Gupta and Anand (1991) found that on re-evaluation

8 out of 13 infants with risk factors, who had failed on BAER earlier, had developed normal

thresholds and by 6 months follow-up, only 3% had hearing loss. Misra, Katiyar, Kapoor,

Shukla, Malik, and Thakur (1996) reported BAER abnormalities and their reversibility in

neonates with birth asphyxia.

It is evident that infants with risk factors are likely to have varieties of abnormalities in

auditory system which might vary from permanent severe hearing loss to normal hearing;

reversible audiological test results in Auditory Maturational Delay (AMD) and Auditory Dys-

synchrony (AD) of different degrees. An appropriate test protocol is essential to differentiate one

pathological condition from other as it not only aids to the early appropriate rehabilitation but

also adds to appropriate counseling to the parents.

Need for the study:

Most authors agree that from 2-15% of infants with hearing loss may exhibit auditory

neuropathy; that is, one can expect to identify auditory neuropathy in approximately 1-3 infants

per 10,000 births (Rance, et al., 2003; Sininger, 2002). The great majority of infants with

auditory neuropathy exhibit one or more high risk factors including blood transfusion,

hyperbilirubinemia, anoxia, low birth weight, NICU residence or family history (Berlin, et al.,

1998).

Numerous researchers reported (Raj, Gupta & Anand, 1991; Berlin, Morlet and Hood,

2003) and cautioned clinicians that infants with risk factors have reversible features of auditory


116

dys-synchrony. Thus it becomes all the more important for us to be able to differentiate such

conditions (AMD) from AD which is most often irreversible. But it is difficult to identify the

exact nature and type of hearing loss in infants and toddlers with risk factors using test protocol

including ABR, BOA, OAE and Immittance as they present with a conflicting test results in a

single assessment. So an appropriate test battery becomes essential in order to differentiate these

mimicking conditions.

It may be recalled that during the neural development dendritic arborization and

synaptogenesis occur. Due to auditory deprivation the synapses lose their function or die which

might lead to absence of LLR in most of the adult cases with AD. However, it is likely that if

LLR is administered during synaptogenesis one might observe LLR in most of the infants. Lee,

McPherson, Yuen and Wong (2001) reported of two cases (school going children) with AD, one

with absent MLR and present LLR while the other had presence of both MLR and LLR (N1/P2).

Thus, LLR could be useful tool to identify and differentiate different conditions in children with

risk factors, if not all, at least most of the clients.

Aim of the study: Thus the study was taken up with the aim to check the importance of LLR in

pediatric hearing assessment especially to differentiate AMD from AD and permanent hearing

impairment.

Method

Subjects:

55 infants/toddlers (30 males and 25 females) were taken for the study with age below 2

years at the time of first evaluation. The subjects included both, those with risk factors which are

associated with hearing impairment and also those who did not demonstrate any such risk

factors. The family history of congenital or acquired hearing loss at an early age was also

specifically looked for in these subjects.

Apart from this all the subjects were also distributed into 4 groups based on the results of

ABR and LLR irrespective of presence or absence of risk factors for further analysis. Group I

was assigned those subjects who had both ABR and LLR present whereas Group II and III

consisted of those with ABR absent – LLR present and ABR present at least in second or third

evaluation– LLR absent in first evaluation respectively. The final group, Group IV comprised of

those subjects who had neither ABR nor LLR present. The number of subjects that formed a part

of Groups I, II, III and IV, was 18, 14, 10 and 13 respectively.

Instrumentation:

1. A calibrated two-channel diagnostic audiometer OB922 with impedance matched speakers was

used to obtain behavioral responses (BOA)

2. Transient Evoked Oto-Acoustic Emissions (TEOAE) were acquired using ILO292 (software

version 5) in full TE menu option in order to examine the status of the outer hair cells to rule

out absence or abnormal Auditory Brainstem Responses (ABR) due to cochlear pathology.


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3. Intelligent Hearing System (HIS) Smart EP version 3.86USBeZ was used to obtain Auditory

Brainstem Responses (ABR) and Long Latency Potentials (LLR) to check the integrity of

neural pathway at the levels of brainstem and cortex respectively.

4. An immittance meter, Grason Stadler Inc. (GSI) Tympstar was used to rule out the presence of

middle ear pathology causing absence of TEOAE or prolongation of ABR wave latencies.

All the instruments were checked for calibration prior to use on each of the subjects

according to manufacturer‟s recommendations.

Test Procedure:

a. Case History:

Detailed information regarding the history of prenatal, natal and postnatal medical

conditions was secured for each of the subjects. Medical records were looked for to obtain

information regarding risk factors pertaining to congenital or early onset hearing loss like

TORCH infections, neonatal jaundice, birth asphyxia, low APGAR scores, seizures, premature

delivery, low birth weight, drinking of Amniotic fluid at the time of delivery, mother getting

Chicken Pox in the first trimester of pregnancy and Bronchopneumonia. A detailed report

regarding the auditory behavior of the subject at home for various environmental sounds like call

bell, dog bark, voices from TV or radio, pressure cooker whistle etc. was obtained from the

parents or caretakers. Parents were counseled regarding frequent follow-ups and were asked to

look for changes in the auditory behavior and also to report those changes during the next

follow-up visit.

b. Test Battery:

1) Behavioral Observation Audiometry (BOA):

Behavioral responses of the subjects were obtained in sound-field condition using warble

tones or narrow band noise of 500, 1, 2 and 4 KHz and also speech stimuli. It was carried out in a

double-room situation. The subjects were seated on the caretakers lap at a distance of 1 meter

from the speakers and at an azimuth of 45° in the observation room. The stimuli were presented

sequentially and the starting level was decided based on the parental report about the auditory

behavior at home. The lowest levels of presentation of each of the stimuli at which the subject

exhibited some sort of auditory behavior was noted down.

2) ABR and LLR:

Single channel ABR and LLR were recorded in sleep condition using IHS Smart EP

instrument. The electrodes were placed at Fz (high forehead) for Non-inverting (positive), A1

(left ear mastoid) for inverting or ground and A2 (right ear mastoid) for ground or inverting.

Neo-prep was used for preparing skin at these electrode sites in order to obtain allowable

impedance values. Independent at each site and inter-electrode impedances were maintained

within 5 KΏ. TDH-39 headphones were placed taking care not to dislodge the electrodes from

their positions and the electrode impedances were re-measured to make sure that the impedance


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stayed within the desired levels at each of the electrodes. The parameters used for ABR and LLR

recording have been shown in Table 2 and 3 respectively.

Table 2: Parameters used to acquire ABR

Acquisition Parameter Stimulus Parameters

Sensitivity- 50 µV

Band-pass Filters- Low Pass- 3 KHz

High Pass- 30 Hz

Notch Filter- Off

Artifact Rejection- On

Electrode Montage- A1- Fz- A2

Time Window- 15 msec.

Type of stimulus- Click

Polarity- Rarefaction

Intensity- Variable

Number of stimuli- 1500

Repetition rate- 11.1/sec. (to obtain

better waveform morphology)

Table 3: Parameters used to acquire LLR

Amplifier Set-up Stimulus Parameters

Sensitivity- 50 µV

Band-pass Filters- Low Pass- 300 KHz

High Pass- 1 Hz

Notch Filter- Off

Artifact Rejection- On

Electrode Montage- A1- Fz- A2

Time Window- 750 msec.

Type of stimulus- Click

Polarity- Rarefaction

Intensity- 70 dB

Number of stimuli- 300

Repetition rate- 1.1/sec.

Presence of ABR (wave I or V) at lowest level was taken as threshold and used for

interpretation as wave I is likely to be more prominent in infants. In case of LLR, the latencies of

the two positive peaks (P1 and P2) and the two negative peaks (N1 and N2) were noted

whenever these were present. In case any one or more of these peaks were absent, only the

latencies of the peaks that were present were noted. LLR responses were shown to three

experienced Audiologists to identify the peaks.

Infants with presence of ABR at 30 dBnHL and also presence of LLR were not followed-

up. Only those infants who demonstrated absence of one or both of these potentials in the first

evaluation were asked to follow-up to monitor any changes with development and diagnosis.

3) Oto-Acoustic Emissions (OAE):

TEOAEs were obtained using ILO292 instrument with a foam tip positioned in the

external auditory canal so as to give a flat frequency spectrum across the frequency range. The

stimuli were clicks filtered with a band-pass filter encompassing 500 to 6000 Hz. The duration of

the rectangular pulses (clicks) was 80 µsec. The level was maintained at 80 dBpkSPL in the

external auditory canal and the inter-stimulus interval was kept constant at 20 msec. A total of

260 averages above the automatic noise rejection level of instrument were stored for analysis.

The presentation mode included a series of four stimuli, three at same level and of same polarity

and the fourth of three times the level of either of the three and opposite in polarity. This, called


119

the non-linear averaging, is used for artifact reduction during the response acquisition. The

responses were considered as emissions based on the reproducibility and the signal-to-noise ratio

(SNR). The overall SNR of greater than or equal to +3 dB and the reproducibility of greater than

50% were considered (Dijk & Wit, 1987) for it to be considered as a presence of an echo or

emission.

4) Immittance:

Tympanometric measurements were done using 678 Hz probe tone (since infants and

toddlers have mass dominant middle ear system) or 226 Hz based on the age of the subject at the

time of evaluation. This was done to rule out absence of OAE due to middle ear pathology.

Appropriate probe tips were used to obtain hermetic seal and comfortable pressure for the

subject. The parameters documented were types of tympanogram to go with ear canal volume,

acoustic admittance and the tympanometric peak pressure. The results were also correlated with

the ENT findings.

Result and Discussion

The subjects were divided into four groups based on the presence or absence of ABR and

LLR irrespective of the presence or absence of risk factors to understand the role of LLR in

pediatric hearing assessment. Group I consisted of 18 subjects, Group II of 14, Group III of 10

and Group IV of 13 subjects. The profile includes findings of different tests (BOA, OAE,

Immittance, ABR and LLR) that were administered on each of the subjects who participated in

the study. Table 4 shows the audiological profile of cases who demonstrated presence of both-

ABR and LLR (Group I).

It can be seen in table 4 that subjects 1, 2, 4, 9 and 10 had positive history for risk factors

that are associated with hearing loss. Subjects 1, 2, 4 and 10 had history of Neonatal Jaundice

(NJ) that did not require blood transfusion. In addition to NJ subject 2 also reported of delayed

birth cry by 1 minute, Neonatal Meningitis (NM) and Febrile Seizures at the age of 2 months.

Subject 9 had history of delayed birth cry by 1 minute without other associated complications. In

spite of presence of risk factor/factors that have been found to be associated with hearing loss in

literature these subjects‟ audiological results fall well within normal limits for BOA, OAE, ABR,

Immittance and LLR except for subjects 4 and 9 who showed absence of OAE and slightly

elevated BOA values for FM tones and speech stimuli. Occurrence of conductive pathology as

indicated by B-type Tympanogram and positive history of ear discharge might have resulted in

abnormal OAE and BOA results in these two subjects. This group was considered to have

normal hearing based on the test battery result except for subject 4 and 9 as they had conductive

component.


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Table 4: Audiological Profile of subjects with ABR and LLR present (Group I)

„P‟ - „present‟; „Ab‟ - „absent‟; „T‟- „tone‟; „S‟ - „speech‟; „R‟-„right‟ and „L‟ - „left‟ ear

The youngest age of the subject in whom LLR could be recorded was 16 days and all the

components of LLR (P1, N1, P2, and N2) were found to be present in this subject. It has also

been reported by McPherson, Tures, and Starr (1989) that LLR or at least a component of LLR

can be present in normal hearing infants even at birth. Though all the components of LLR could

be recorded in the subject 12, it is not always necessary that all the LLR components would be

observable at birth. But there is high possibility of presence of at least one of the LLR

components at high intensity if the infants follow normal developmental pattern. Thus, it

suggested that LLR might be able to substitute ABR provided the normative data is established

for this population and also the relationship between the behavioral and LLR threshold is

established.

Some time LLR might be a better tool for assessing hearing sensitivity when there is mild

degree of dys-synchrony which might lead to noisy ABR morphology but might show better

LLR responses. This might help to identify hearing sensitivity in such cases. 5 subjects had

undergone three evaluations each at a interval of 3 months or more between two follow-ups and

also 2 subjects who underwent two evaluations apiece at interval of three months or more. Rest

of the 7 subjects underwent only 1 evaluation each. This group showed interesting finding of

absence of ABR peaks even at 90 dBnHL in spite of BOA showing normal hearing in most of

the subjects to severe hearing loss in subjects 1 and 3. However, all the subjects showed A-type

Sub Risk

Factors

BOA Level

(dBHL)

Tympanogram

Type

OAE ABR Threshold

(dBnHL)

LLR at 70

dBnHL

T S R L R L R L R L

1 P 40-55 35 A A P P 30 30 P P

2 P 45-50 40 A A P P 30 30 P P

3 Ab 35-50 35 A A P P 30 30 P P

4 P 50-65 50 B B Ab Ab 50 40 P P

5 Ab 40-55 40 As As Ab Ab 40 40 P P

6 Ab 40-55 40 A A P P 30 30 P P

7 Ab 45-50 45 A A P P 40 40 P P

8 Ab 35-45 30 As As P P 30 30 P P

9 P 50-60 45 B B Ab Ab 50 50 P P

10 P 50-55 40 A A P P 30 30 P P

11 Ab 35-45 35 A A P P 30 30 P P

12 Ab 30-45 30 A A P P 40 40 P P

13 Ab 30-40 35 A A P P 30 30 P P

14 Ab 45-55 45 A A P P 50 50 P P

15 Ab 35-40 30 A A P P 30 30 P P

16 Ab 35-40 30 A A P P 35 40 P P

17 Ab 35-40 30 A A P P 30 30 P P

18 Ab 30-40 30 A A P P 30 30 P P


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tympanogram in presence of recordable TEOAE and presence of LLR at 70 dBnHL. Considering

that the maturation of auditory system occurs from peripheral to central (auditory nerve to

auditory cortex) (Romand, 1983; Montandon, Cao, Engel & Grajew, 1979; Stockard & Stockard,

1981, 1983), ABR also should have been present if LLR were to be present. But this was not to

be in these subjects which gives an indication towards some permanent abnormality at the level

of Auditory Nerve and Brain-stem which contain the generators for different ABR peaks. ABR is

actually a test of neural synchrony and is dependent upon the ability of neurons to maintain

precise timing and respond synchronously to external stimuli (Jewett & Williston, 1971). So the

absence of ABR peaks could be because of dys-synchronous firing of the ANFs or in other

words, Auditory Dys-synchrony (AD). LLR requires much lesser degree of synchrony of firing

of the ANFs (Kraus, et al., 2000) which is why probably it was found to be present in these

subjects. The physiology behind this aspect has been reported by Kraus et al. (2000). The cortical

potentials reflect neural synchrony differently than ABR. The ABR peaks reflect synchronous

spike discharge generated in the nerve tracts whereas the peaks in cortical responses reflect the

summation of excitatory post-synaptic potentials. In other words the ABR reflects action currents

in axons while the cortical potentials reflect slow dendritic events. Because unit contributions to

the ABR are biphasic and of short duration ABR peaks tend to cancel when discharges are

separated by fractions of a millisecond. In contrast, for cortical potentials, the waves are so slow

that contributions separated by several milliseconds contribute to these later waves. While the

ABR reflects highly synchronous discharge with millisecond precision the synchrony required

for cortical potentials is on the order of several milliseconds.

This highlights that after 3 evaluations in 5 subjects it was possible to label them as

having AD. In the first evaluation itself ABR was found to be absent and LLR present which

prompted to diagnose the subjects as having AD. The follow-up testing was done only to confirm

this status. All other subjects in the group were suspected to have AD based on similar findings

in the first or first two evaluations but they could not be followed up owing to time constraint or

their inability to come for follow-up. Thus we may be able to arrive at the diagnosis of infants or

toddlers having AD after the first evaluation itself if ABR is absent but LLR present. This also

receives support from Starr, Picton, Sininger, Hood and Berlin (1996) who reported presence of

LLR in the subjects with Auditory Neuropathy which is more recently being called AD.

Subjects 3, 5, 6, 8 and 9 had absence of TEOAE which could be accounted by As-B, As-

B, B-B, As-As, and As-As type of tympanogram respectively suggesting presence of conductive

pathology in these subjects. The conductive pathology hampers the reverse transmission of OAE

through the middle ear system and thus prevents the OAE from being recorded at the level of ear

canal. If LLR was not done it would not have been possible to categorize these subjects into AD

as most of the available literature on AD highlights the presence of OAE being an integral part of

the test battery for its identification. Thus, it goes to show how important can LLR be in

identifying AD in infants and toddlers at an early age even if OAEs are absent owing to some

middle ear problem. This can implicate in early and appropriate use of intervention strategies or

measure like cochlear implantation can be taken very early in life as the literature supports the


122

usefulness of cochlear implantation in cases with AD (Peterson et al., 2003 cited in Kirk, Firszt,

Hood, and Holt, 2006).

Also in subject 10 there is presence of ABR at 90 dBnHL only which suggests a milder

degree of dys-synchrony in the ANFs‟ firing. LLR was found to be present at 70 dBnHL in this

subject. Hyde (1997) found 10 dB discrepancy between the LLR threshold in asleep condition

and the behavioral threshold (LLR threshold> Behavioral threshold) and suggested about 10-15

dB discrepancy between ABR threshold and behavioral threshold (ABR threshold> Behavioral

threshold). This implies that LLR and ABR thresholds should roughly coincide which is not

what was found in subject 10. This subject showed a discrepancy of grater than or in worst case

equal to 20 dB between ABR and LLR. Also, BOA responses were observed at 45-55 dB and 45

dB for FM tones and speech respectively which suggests that the subject was hearing sounds at

much lower intensities than suggested by ABR finding. All this in conjunction led to this subject

being put in the category of having AD (i.e., Group II). The inclusion of this case in this group

also receives support from Sininger (2002) who said that the neural response (ABR) will be poor

or completely absent but will occasionally show a small wave V response (at high stimulus

intensities). However, the subject did not come for follow up to confirm the diagnosis. Since

LLR requires lesser synchrony than ABR, even small amount of demyelinization might have led

to its presence whereas a small amount of demyelinization of lower structures (auditory nerve

and brainstem) could have produced synchronous firing only at much higher level (90 dBnHL).

So, this could even be classified in to AMD. But due to lack of information about further follow-

up it can only be a matter of debate whether to call it AD or AMD. So if such cases are

encountered follow-up evaluations are advisable to confirm the actual existing condition.

Apart from this Group II comprised of 8 subjects out of a total of 14, who had history of

risk factor/factors. These were subjects 4, 6, 7, 8, 10, 12, 13 and 14. Subjects 4, 6, 10, 12 and 13

had history of Neonatal Jaundice but only 4 and 13 required blood transfusion and phototherapy

respectively. Subject 8 demonstrated multiple risk factors in terms of history of mother having

Chicken Pox in the first trimester of pregnancy, consumption of amniotic fluid by the subject at

the time of delivery, low blood sugar level at the time of birth and febrile seizures at 1 month of

age. Subject 10 also had the history of birth asphyxia to go with neonatal jaundice and subject 14

had birth asphyxia followed by seizures few days later. So in all, 55.55% of the subjects clubbed

under the AD group (Group II) had history of severe degree of risk factor/factors pertaining to

hearing loss. Thus, it suggests that severe degree of risk factors showed-up in high chances of

auditory abnormality and hence such infants and toddlers must be considered for detailed

audiological evaluation and LLR must be the part of the test battery to identify AD.

Group III consisted of 10 subjects 4 of whom had history of one or more risk factors that

have been suggested to cause hearing loss. Subject 1 and 3 had history of neonatal jaundice to go

with seizures in early infancy whereas subject 9 had history of premature delivery. Subject 8 was

confronted with multiple risk factors that included birth asphyxia, low APGAR scores,

bronchopneumonia, and seizures.


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Six (1, 3, 6, 8, 9, and 10) out of the total of 10 subjects of this group showed presence of

OAE in absence of any recognizable ABR peak even at 90 dBnHL in first recording. Based on

the reports in literature that talk of absence of ABR in presence of OAE being the feature of AD

(Starr et al., 1996), these subjects could have been diagnosed as having AD. But follow-up test

results in these subjects (second follow-up for subjects 3, 6 and 10 and second and third follow-

ups for subjects 1, 8 and 9) suggested other wise. These follow up recordings demonstrated

presence of ABR and gradual progression towards normalcy in terms of peak latencies in those

with two or three evaluations. These recordings also showed absence of LLR in presence of ABR

in first recording itself which is a big indicator that the maturation has not fully occurred at the

central level (at the level of cortex). The routine audiological testing (which includes BOA,

ABR, OAE and immittance) in such cases, give the findings that are similar to the findings in

cases with AD (i.e., absent ABR, near normal or slightly elevated BOA, A-type tympanogram

and present TEOAE) at least in first evaluation. This can lead to a case being misdiagnosed as

AD though it could be a case of delayed maturation (Auditory Maturational Delay or AMD).

Comparison of the profiles of subjects in Table 2 and 3 can give a valuable introspection in this

regard. The presence of LLR in absence of ABR gives an indication towards normal cortical

functioning in lieu of sub-normal or abnormal peripheral (auditory nerve and brain-stem)

functioning. Based on the earlier discussion with regard to table 2, the label of AD (based on

peripheral-to-central course of maturation) can safely be put forth for such cases. Absence of

LLR, when ABR is present (normal or abnormal) or when it is absent, shows a trend towards

either AMD or severe hearing loss. But it would be better if cases with such findings are

monitored with regard to the changes in auditory behavior at home and also through regular

follow up (preferably at 3 months intervals) till a clearer picture of the condition evolves

(preferably upto 2 to 3 years of age), more so if OAEs are absent.

In subjects 4 and 6 again, the absence of OAE can be accounted by B type tympanogram

in both ears of both the subjects. These have been considered in this group based on the BOA

findings which suggests near normal responses to FM tones and speech in subject 4 and shows a

maturational course, indicated by improvement in response levels in second evaluation, in

subject 6. So, if ABR is present at any level and LLR is absent in the first evaluation itself the

case can be diagnosed as AMD if OAEs are found to be present. This receives support from the

findings of 4 out of 6 subjects in table 3. These subjects (1 and 8 in third evaluation and 9 and 10

in second evaluation itself) showed the presence of LLR and also improvement in the ABR peak

latencies with increase in age, thus, supporting the diagnosis of AMD which was established

based on absence of LLR in the first recording session itself.

Rest of the subjects (2, 4, 5, and 7) had undergone only one evaluation. They had

presence of ABR and OAE, except subject 4 (absent OAE), but LLR was absent. Absence of

OAE could be accounted based on the tympanometry result which showed B-type tympanogram

in subject 4. Presence of ABR and absence of LLR helped in the diagnosis of AMD in these

subjects. However, follow-up is required to confirm this diagnosis. It has been seen that absence

of ABR in the first evaluation could be misleading as there can be case of delay in maturation


124

that lead to this phenomenon. This paradox can easily be solved by the inclusion of LLR in the

test battery for the hearing assessment in infants and toddlers. Thus, it is strongly recommended

to include LLR in the protocol for assessing hearing in infants and toddlers.

In Group IV (ABR absent- LLR absent) 3 out of a total of 13 subjects (23.08%) had

history of one or more risk factors pertaining to hearing loss. Subject 1 had history of neonatal

jaundice, subject 13 had birth asphyxia and subject 8 had a cluster of risk factors that included

prenatal high blood pressure (at 7th

month), premature delivery and low birth weight. All the

subjects had BOA responses at much higher levels than normal hearing infants which correlated

well with the findings that included absence of OAE, A-type tympanogram (except subjects 1, 2,

and 9 in first recording and subjects 1 and 7 in second recording in both and left ear respectively)

and no repeatable peaks in ABR and LLR recordings. Absence of LLR along with absence of

OAE and ABR gives a fair indication towards subjects having permanent hearing loss. A

conductive component in subjects 1, 2, 7 and 9 cannot account for absence of ABR at 90 dBnHL

and that of LLR at 70 dBnHL. Thus, this group of subjects can be diagnosed as having

permanent hearing loss.

The differentiation between the two- AMD Vs severe hearing loss can be easily

accomplished based on TEOAE findings. If the TEOAEs are present it shows that the course of

maturation may be slightly prolonged or delayed causing abnormality in ABR and LLR findings

whereas absence of TEOAE would indicate abnormality at the level of cochlea too and hence

severe hearing loss could be a better recommendation.

It can be concluded based on the results that LLR is an important tool in differential

diagnosis of different conditions that are likely to be encountered when dealing with the hearing

assessment of pediatric population of less than 2 years of age. The same can be clearly

understood from the table 5.

Table 5: Different test results and diagnosis based on them

BOA Immittance OAE ABR LLR Diagnosis

1. Normal A-type Present Present Present Normal hearing

2. Normal A-type Present Absent Present AD

3. Normal A-type Present Absent/

Abnormal/

Present

Absent AMD

4. Abnormal A-type Absent Absent Absent Severe hearing loss

The test results in case of AMD and AD are identical if LLR results are taken away. The

Audiologist will, hence, find it very difficult to diagnose the condition or, more realistically,

would have to wait until the maturation has fully occurred. This difficulty can be overcome when

LLR results are included. The absence of LLR can be considered for the diagnosis of AMD

whereas its presence can be termed as AD (based on the pattern of maturation which suggests


125

peripheral to central course for it) based on presence of ABR at any level and absence of ABR

even at high levels respectively. Thus LLR can prove to be of immense importance in differential

diagnosis of AD and AMD. Also, though other routine audiological tests indicate hearing

sensitivity within normal limits, still there may be a case of delayed maturation at higher centers

(auditory cortex). This can be ruled out by presence of LLR. Not only that, LLR can also be used

as a substitute for ABR to obtain threshold especially if ABR morphology is poor or if ABR is

completely absent as in cases with AD. LLR can also be used as supporting tool for the diagnosis

of severe hearing loss. Absence of LLR would indicate minimum or no signal reaching the

auditory cortex that can evoke a cortical response.

The normative data was also established in the present study for ABR but due to lack in

number of subjects a more careful usage of these findings is recommended. In case of LLR

norms, large variability was observed across the subjects. So it is recommended that the

interpretation of LLR wave be cautiously approached especially with regard to the absolute

latency. It is also recommended that rather than looking at the latency it would be better to look

for the presence or absence of LLR for the differential diagnosis of different conditions.

Implications of the study:

First and foremost, the study highlights the importance of LLR in differential diagnosis of

AMD from AD and permanent hearing loss. So this brings out a solution to the paradoxical

nature of hearing assessment in infants and toddlers. The study also suggests the use of LLR in

threshold estimation especially if there is case of AD in which ABR is absent and thus implicates

in early decision for cochlear implantation and avoid unnecessary psychological trauma to the

parents if it is AMD. The study also tried to establish norms for ABR and LLR which could be

used for arriving at conclusion if an infant or toddler is developing normally or not, though a

careful use of the findings of the present study is recommended.

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Hyde, M. (1997). The N1 response and its applications. Audiology & Neuro-otology, 2(5), 281-

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Jewett, D. & Williston, J. S. (1971). Auditory evoked far fields averaged from the scalp of

humans. Brain, 94, 681-696.

Kirk, K. I., Firszt, J. B., Hood, L. J. & Holt, R. F. (2006). New directions in pediatric cochlear

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Lee, J. S., McPherson, B., Yuen, K. C. & Wong, L. L. (2001). Screening for auditory neuropathy

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potentials and middle latency auditory evoked potentials in infants and adults.

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Moore, D. R. (1985). Post natal development of the mammalian central auditory system and the

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19-30.

Quigley, S. P. (1978). The effects of early hearing loss on normal language development. In F.

N. Martin (Ed.). Pediatric Audiology. Englewood Cliffs NJ: Prentice Hall.

Raj, H., Gupta, A. K. & Anand, N. K. (1991). Hearing assessment by brainstem auditory evoked

responses (BAER) in neonates at risk. Indian Pediatrics, 28, 1175-1183.

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Roberts, J. L., Davis, H., Phon, G. L., Reichet, M. D., Sturtevant, B. S. N. & Marshall, M. D.

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http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Search&itool=pubmed_AbstractPlus&term=%22Montandon+PB%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Search&itool=pubmed_AbstractPlus&term=%22Cao+MH%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Search&itool=pubmed_AbstractPlus&term=%22Engel+RT%22%5BAuthor%5D

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Search&itool=pubmed_AbstractPlus&term=%22Grajew+T%22%5BAuthor%5D


127

Pitch perception in individuals with sensorineural hearing loss with

and without dead regions

Palash Dutta & K Rajalakshmi

Abstract

It has been suspected that a pure tone might be perceived as noise like when the tone

produces maximum excitation in a region of the cochlea where there is extensive or complete

loss of inner hair cell (IHC) and /or neural function which is referred to as a dead region (DR).

It is defined as region in the cochlea where IHCs and /or neurons are functioning so poorly that

a tone producing peak vibration in that region is detected by off place listening (i.e. the tone is

detected at a place where the amount of basilar membrane vibration is lower but IHCs and

neurons are functioning more effectively). In this study total 17 sensorineural hearing loss

individuals with and without dead region were taken. They were divided into two groups-

subjects having sensorineural hearing loss with dead region and without dead region. For

detection of dead regions psychophysical tuning curves (PTCs) was established using a

procedure which is similar to the physiological determination of a tuning curve on the basilar

membrane or in the auditory nerve. TEN (Threshold-Equalizing Noise) test was also used which

is relatively fast and simple test. If the subjects had dead region or not then pitch matching

experiment was carried out. For the pitch matching task subjects were asked to match the

perceived pitch of a variable pure tone with that of another pure tone that was fixed in

frequency. The results reveal that pitch perception in individuals with sensorineural hearing loss

with dead region is different than in those individuals having sensorineural hearing loss without

dead region. The result also shows that if sensorineural hearing loss is accompanied with dead

region (DR) then there is broader auditory filter and hence pitch matching is difficult.

Introduction

A sinusoid is usually perceived by people with normal hearing as having clear tonal

quality and a distinct single pitch; hence sinusoids are often called pure tones. However some

people with hearing impairment report that pure tones sound highly distorted and noise like

(Florentine & Houtsma, 1983; Moore et al. 1985; 1977b; Murry & Byrere, 1986; Huss & Moore,

2005). From the audiogram it is difficult to predict whether or not a person will experience such

a percept. It has been suspected that a pure tone might be perceived as noise like when the tone

produces maximum excitation in a region of the cochlea where there is extensive or complete

loss of inner hair cell (IHC) and/or neural function which is sometimes referred to as a dead

region (DR) (Florentine & Houtsma, 1983; Moore et al, 1985; Huss & Moore, 2005). A DR can

be defined as a region in the cochlea where IHCs and/or neurons are functioning so poorly that a




128

tone producing peak vibration in that region is detected by off-place listening (i.e. the tone is

detected at a place where the amount of basilar-membrane vibration is lower but the IHCs and

neurons are functioning more effectively; Moore, 2004). The extent of a DR can be defined in

terms of the characteristic frequencies (CFs) of the IHCs and/or neurons immediately adjacent to

the DR (Moore, 2001). DRs can be diagnosed and localized using psychophysical tuning curves

(PTCs) (Florentine & Houtsma, 1983; Turner et al. 1983; Moore et al. 2000; Moore & Alcantara,

2001; Huss & Moore, 2003; Kluk & Moore, 2005) and using the threshold-equalizing noise

(TEN) test (Moore et al, 2000; 2004; Huss and Moore, 2003).

The Pitch of a pure tone may be determined by the auditory system from the distribution

of activity or excitation along the basilar membrane or in the auditory nerve (place theory)

(Helmholtz, 1863; von Bekesy, 1960; Siebert, 1968, 1970) or from temporal information derived

from patterns of phase locking in the auditory nerve (Siebert, 1970; Moore, 1973; Goldstein &

Srulovicz, 1977; Srulovicz & Goldstein, 1983).

In principle, theories of pitch perception can be evaluated by studying pitch perception

for people with hearing impairment (Moore & Carlyon, 2005). Studies investigating pitch

perception in subjects with low-frequency DRs have suggested that a tone with a frequency

falling in a DR is often perceived with a low pitch that is roughly “normal” (Florentine &

Houtsma, 1983; Turner et al., 1983). Pitch shifts were much smaller than would be predicted

based on the place where the tone was assumed to be detected (Just outside, the boundary of the

DR). The results were interpreted as indicating that the pitch of a low frequency tone is

predominantly derived from the temporal pattern of neural firing evoked by the tone.

The results obtained by Florentine and Houtsma (1983) and by Turner et al. (1983) were

mostly based on pitch matches using tones at and within about 2 octaves of the edge frequency

of the DR. It is possible that the analysis of information about pitch carried by interspike

intervals is optimized when place and temporal information is consistent (Evans, 1978). For

example, the analysis of temporal information may depend upon differences in the phase of the

response at different points along the basilar membrane (Loeb et al., 1983; Shamma & Klein,

2000; Carney et al., 2002). The processing of temporal information could be disrupted when the

propagation time of the traveling wave along the basilar membrane deviates from normal as may

happen in hearing impaired ears (Ruggero et al., 1996). When a tone produces peak vibration in

a DR perception of the tone depends on the spread of vibration to an adjacent functioning region

of the cochlea. At that region, the traveling wave pattern and specifically the relative phase of the

response at different places, might differ markedly from the pattern occurring around the place

where peak vibration occurs. This might markedly disrupt the processing of temporal

information.

It remains unclear as to what determines the pitch when either temporal and place

information become weaker and what happens when temporal and place codes give conflicting

information about pitch. The presence or absence of dead regions can have serious implications

for the fitting of hearing aids. Amplification over a frequency range corresponding to a dead


129

region may not be beneficial because amplified frequency components would be detected and

analyzed in frequency channels that normally respond to other frequencies.

The present study aimed to investigate the pitch perception in individual with and without

dead regions in subjects with sensorineural hearing loss and whether there is relationship

between dead region and perceived pitch. The study also investigated whether there is any

relationship between the extent of DRs and pitch shift.

Method Participants

Participants were divided into 2 groups. In first group 7 subjects having sensorineural

hearing loss without dead region were taken. In the second group 10 subjects having

sensorineural hearing loss with dead region were taken. Sensorineural hearing loss without dead

region group subjects had no significant history of neurological disorders. Subject had pure tone

threshold more than 40 dBHL in frequency ranges 250 Hz to 4000 Hz and immittance screening

revealed no middle ear pathology. Subjects‟ air bone gap was less than 10 dBHL at all

frequencies from 250 Hz to 4000 Hz. Subject had pure tone average more than or equal to

moderate degree of hearing loss and immittance screening revealing no middle ear pathology.

Instrumentation

A calibrated two channel diagnostic audiometer MA-53 was used for testing the subjects.

An immittance audiometer (GSI-33) used for evaluation of middle ear function. Tape recorder

with CD for TEN test was connected to a two channel diagnostic audiometer for presenting the

stimulus. Test was carried out in an air conditioned sound treated double room set up with

ambient noise levels within permissible limits (Re: ANSI 1991, as cited in wilber, 1994).

Test materials

TEN test CD was used for the purpose of diagnosing dead region in subjects with sensorineural

hearing loss.

Procedure

1) Pure Tone average: Pure tone thresholds were obtained at octave frequencies between 250

Hz and 8000 Hz for air conduction stimuli and between 250 Hz to 4000 Hz for bone conduction

stimuli using modified Hughson Westlake method (Carhart & Jerger, 1959).

2) Tympanometry: Tympanometry and reflexometry were carried out to rule out any middle ear

pathology.

3) Psychophysical tuning curves: Psychophysical tuning curves (PTCs) (Chistovich, 1957;

Small, 1959) were measured using a procedure which is similar to the physiological

determination of a tuning curve on the basilar membrane (Sellick, et al., 1982) or in the auditory

nerve (Kiang, Watanabe, Thomas & Clark, 1965). The signal was a sinusoid which was

presented at a level 10 dB above the absolute threshold. In a given run the signal frequency was


130

fixed. The masker was an 80 Hz wide band of noise with variable center frequency. The exact

masker frequencies were chosen individually for each subject so as to define the position of the

tip of the tuning curve with reasonable accuracy. Several signal frequencies were used for each

subject; they were chosen to cover a range including any suspected dead region. For each of

several masker center frequencies the level of the masker needed just to mask the signal was

determined.

4) TEN (Threshold-Equalizing Noise) test: For detection of dead regions TEN test was used

which is relatively fast and simple test (Moore, et al. 2000). The test makes use of a masking

noise called “threshold-equalizing noise” (TEN) which is spectrally shaped.

Absolute thresholds and masked thresholds in TEN were measured using manual

audiometry with the procedure proposed by Carhart and Jerger (1959). The TEN from the CD

was fed to one of the tape inputs on OB 922 audiometer and the sinusoidal test signal was fed to

the other. TEN and signal levels were controlled by the use of the level controls on the

audiometer. The noise and sinusoidal signal were mixed using the audiometer, and stimuli were

delivered using TDH - 39 earphones supplied with audiometer. Each ear of each subject was

tested separately.

Pitch-matching Procedure

For the pitch matching task subjects were asked to match the perceived pitch of a variable

pure tone with that of another pure tone that was fixed in frequency. The two tones were

presented alternatively. Matches were made within the same ear to estimate the reliability of

matching. The subject was instructed to say „same‟ or „different‟ in the perceived pitch of

variable tone with that of fixed frequency tone. The procedure was carried out for frequencies at

250, 500, 1000, 2000 & 4000 Hz. Data was tabulated in terms of the perceived pitch at the above

frequencies. The extent of pitch matching was noted down for each frequency in all the subjects.

Results and discussion

There were 10 subjects with sensorineural hearing loss with dead region and 7

sensorineural hearing losses without dead region in the present study.

A) Group analysis

Table 1a &1b: Cross tabulation with respect to fixed and variable frequency in SNHL without dead region

1(a) Right ear

Fq. In Hz 250 500 1000 2000 4000

250 7 0 0 0 0

500 0 7 0 0 0

1000 0 0 7 0 0

2000 0 0 0 7 0

4000 0 0 0 0 7

# fixed frequency is shown in the first column and variable frequencies in other 5 columns


131

Number of subjects perceiving each fixed frequency and variable frequency are presented

as a cross table for both the groups and both the ears. Since we are dealing with frequency data

test of significance were not suitable and there was possibility of one person perceiving in more

than one way and because of this constraint the analyses were restricted to graphical

representation.

1 (b) Left ear

Fq. In Hz 250 500 1000 2000 4000

250 7 0 0 0 0

500 0 7 0 0 0

1000 0 0 7 0 0

2000 0 0 0 7 0

4000 0 0 0 0 7

# Fixed frequency is shown in the first column and variable frequencies in other 5 columns

Table 2a & 2b: Cross tabulation with respect to fixed & variable fq in SNHL with dead region

2(a) Right ear

Fq. In Hz 250 500 1000 2000 4000

250 10 1 1 - -

500 - 10 1 - -

1000 1 2 9 4 2

2000 1 2 4 10 9

4000 - 1 3 8 9

2(b) Left ear

Fq. In Hz 250 500 1000 2000 4000

250 10 1 1 - -

500 - 10 2 - -

1000 - 1 10 4 3

2000 1 1 3 9 7

4000 - 1 3 7 9

# Fixed frequency is shown in the first column and variable frequencies in other 5 columns

Number of subjects was converted as percentage since the subject size was not similar in

both the groups. For the first group sensorineural hearing loss without dead region 7 subjects

were taken and for second group sensorineural hearing loss with dead region 10 subjects were

taken.

1) Sensorineural hearing loss without dead region right ear group and left ear group

It can be observed from the graph that all 7 subject with sensorineural hearing loss

without dead region in both right ear and left ear fixed frequency same as variable frequencies at

all frequency levels. None of the subject perceived in any other frequency level.


132

Figure 1: Sensorineural hearing loss without dead region (Right ear)

Figure 2: Sensorineural hearing loss without dead region (Left ear)

2) Sensorineural hearing loss with dead region right ear group and left ear group

It can be noticed that in each fixed frequency we can find subjects who perceived in other

variable frequencies but most of the subjects could perceive at the same frequency.

Figure 3: Sensorineural hearing loss with dead region (Right ear)


133

Figure 4: Sensorineural hearing loss with dead region (Left ear)

Cochlear hearing loss results in a variety of changes in the way that sounds are

represented in the auditory system. For such changes are especially relevant for the perception of

pitch. There may be regions within the cochlea where the inner hair cells (IHCs) and/or neurons

are completely nonfunctional. These are referred to as dead regions. The peak in the neural

excitation pattern may occur at a place very different from that normally associated with that

frequency. The place theory predicts that the perceived pitch of the tone in such a case should be

very different from normal.

The result of present study indicated that pitch perception in individual with sensorineural

hearing loss with dead region is different than the sensorineural hearing loss without dead region.

The result in pitch shifts are for two reasons. The first applies when the amount of hearing loss

varies with frequency and especially when the amount of inner hair cell (IHC) damaged varies

with characteristic frequency. When the IHC transduction efficiency is reduced and so a given

amount of basilar membrane (BM) vibration leads to less neural activity than when the IHCs are

intact. When IHC damage varies with characteristic frequency the peak in the neural excitation

pattern evoked by a tone will shift away from a region of greater IHC loss. Hence the perceived

pitch is predicted to shift away from that region. Early studies of diplacusis (De Mare, 1948;

Webster & Schubert, 1954) were generally consistent with this prediction, showing that when a

sinusoidal tone is presented in a frequency region of hearing loss, the pitch shifts towards a

frequency region where there is less hearing loss. An alternative way in which pitch shifts might

occur is by shifts in the position of the peak excitation on the BM.

The results of the present study indicated that the tips of tuning curves shifted towards

lower frequencies in case of sensorineural hearing loss with dead region. This means that the

maximum excitation at a given place is produced by a lower frequency. The results also showed

shift of pitch toward higher frequency (upward) but some cases showed shift towards lower

frequency. The peak of the BM response in an impaired cochlea would be shifted towards the

base –i.e toward place normally responding to higher frequencies. Gaeth and Norris (1965) and

Schoeny and Carhart (1971) reported that pitch shifts were generally upwards regardless of the

configuration of loss. However it is also clear that individual differences can be substantial and


134

subjects with similar patterns of hearing loss (absolute thresholds as a function of frequency) can

show quite different pitch shifts. Huss, et al. (2001) and Huss and Moore (2005) obtained pitch

matches and octave matches for subject with an extensive high frequency dead region. For tones

whose frequency fell well within the dead region the perceived pitch was shifted upwards

although it was also unclear.

The result of the present study indicated that frequency discrimination is poor for the

individual with sensorineural hearing loss with dead region. The frequency of pure tones may be

represented in terms of phase locking (a temporal representation) for frequencies below about

5000 Hz and purely spectrally (a place representation) for higher frequencies.

The precision of phase locking can be reduced (Wolf et al. 1981; Miller, et al. 1999),

although this has not always been found. According to temporal theory reduced precision of

phase locking should adversely affect frequency discrimination.

The propagation time of the traveling wave along the basilar membrane and the relative

phase of the response at different places may differ from normal because of loss of the active

“mechanism”, structural abnormalities or both (Ruggero, 1994; Ruggero et al. 1996). This could

adversely affect mechanisms for pitch perception based on cross-correlation of the outputs of

different points on the basilar membrane (Loeb et al. 1983; Shamma, 1985; Shamma and Klein,

2000).

It has been proposed that the frequency discrimination of steady pulsed tones by normally

hearing listeners is largely based on temporal information (cues desired from phase locking) for

frequencies upto 4 to 5 KHz (Moore, 1973, 1974, 2003; Goldstein and Srulovicz, 1977; Sek &

Moore, 1995; Micheyl, et al. 1998, Heinz, et al. 2001). Above 4 to 5 KHz, frequency

discrimination is thought to depend mainly on place based changes in the excitation pattern

(Moore, 1973b; Sek & Moore, 1995) although residual phase locking may play some role

(Heinz, et al. 2001).

The results clearly indicated that if sensorineural hearing loss is accompanied with dead

region (DR) then there is broader auditory filter. If there is no dead region the auditory filter

shape is narrow which might indicate that hair cell in that region could be functioning. It can be

expected that the perception of pitch might be more affected by the relative phase of the

component in a dead region than the without dead region.

For such DR cases frequency selectivity is reduced. Auditory filters are broader than

normal (Pick et al. 1977; Glasberg & Moore, 1986; Moore, 1998). Hence the excitation pattern

evoked by a sinusoid is also broader than normal. According to place theory this should lead to

impaired frequency discrimination of sinusoids. Reduced frequency selectivity also presumably

leads to a reduced ability to resolve partials in complex tones and this might adversely affect the

perception of the pitch of complex tones and also pure tone. For subjects with broad auditory

filters even the lower harmonics would interact at the outputs of the auditory filters giving a


135

potential for strong phase effects. Changes in phase locking and in cochlear traveling wave phase

could also lead to less clear pitches and poorer discrimination of pitch.

In the present study subjects of sensorineural hearing loss with dead region reported that

they did not perceive distinct pitch but sounded like noises. There have been a few studies of

pitch perception in people with hearing losses that increase abruptly at high frequencies, who

probably had dead regions at high frequencies. These subjects often report that high frequency

sinusoids do not have distinct pitch but sound like noises or buzzes (Villchur, 1973; Moore et al.

1985b; Murray & Byrne, 1986). Subjective reports that pure tones sound noise like may be taken

as a hint that a dead region is present but ratings of the clarity of the tonal percept cannot be used

as a reliable indicator of dead regions. A sensorineural hearing loss involves not only a reduction

of sensitivity but also a set of supra threshold impairments that

distort the perception of sounds:

listeners may suffer increased susceptibility to forward and backward masking, making it more

likely that vowels will mask energy in weaker adjacent consonants; auditory filters are often

broader than normal, leading to increased masking by background noises and by echoes in

reverberant rooms; in extreme cases, even in quiet anechoic environments, difficulties

may be

experienced in detecting changes in the pitch of a talker's voice and in determining the spectral

shape of speech sounds; the ability to analyze the temporal fine structure of the output

of auditory

filters may also be reduced leading to difficulties in following rapid changes in amplitude,

frequency and pitch and exacerbating the effects of noise.

Conclusions

From the result we can conclude that pitch matches are often erratic and frequency

discrimination is poor for tones with frequencies falling in a dead region. This indicates that such

tones do not evoke a clear pitch sensation. The shifted pitches found for some subjects indicate

that the pitch of low frequency tones is not represented solely by a temporal code. Possibly there

needs to be a correspondence between place and temporal information for a “normal” pitch to be

perceived.

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unilateral low frequency hearing loss. Journal of the Acoustical Society of America, 73,

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137

Effect of Dichotic Offset Training (Dot) in Children with an

Auditory Processing Disorder

Priya G & Asha Yathiraj

Abstract

Management of children with auditory processing disorders had gained wide importance

in recent years. Various studies in the literature have shown that training children with central

auditory processing problems using deficit specific intervention results in the improvement of

auditory skills. The present study aimed at finding out the effectiveness of Dichotic Offset

Training in children with auditory processing disorder. Twelve children who failed a screening

checklist and the Dichotic CV and/or the Dichotic Digit test were included in the study. Six of

them in the experimental group received Dichotic Offset Training using the training material

developed by Yathiraj (2006). The children in the control group did not receive any training. The

results revealed that there was statistically significant improvement after training in dichotic CV

test. In dichotic digit test statistically significant improvement was seen in right ear single

correct scores alone and not for left ear single correct score and double correct scores. Thus

training children with binaural integration deficits using dichotic Offset Training was found to

be effective.

Introduction

Auditory stimulation is so essential to development of humans that any interruption in

this decoding process may have adverse effects on the overall maturation of an individual. The

presence of an auditory processing problem can disrupt the decoding of auditory signals (Hanson

& Ulvestad, 1979). The current definition of (C)APD explicitly recognizes both the auditory

nature of the disorder and the inherent non-modularity of the central auditory nervous system.

ASHA (2005) defined central auditory processing as “the perceptual (i.e., neural) processing of

auditory information in the central nervous system (CNS) and the neurobiologic activity that

gives rise to the electrophysiologic auditory potentials”. It includes neural mechanisms that

underlie a variety of auditory behaviours including localization/lateralization, performance with

degraded or competing acoustic signals, temporal aspects of audition, auditory discrimination

and auditory pattern recognition.

Recent reports suggest that auditory training (AT) can serve as a valuable intervention

tool particularly for individuals with language impairment and central auditory processing

disorder (C)APD (Chermak & Musiek, 2002). Musiek, Shinn and Hare (2002) noted that the use

of AT for treatment of APD is different from the classic use of AT. Most important to this




138

difference is that AT applied to APD is targeting the brain as the main site of mediation and the

brain, unlike the auditory periphery is plastic.

Training for auditory integration is one such formal training program (Katz, Chertoff &

Sawusch, 1984; English, Martonik & Moir, 2003). It has been shown that providing deficit

specific therapy does result in improvement in auditory processing (Katz et al., 1984; Putter-Katz

et al., 2002; English et al., 2003).

Binaural integration (BI) is the ability of a listener to process information presented to

both ears at the same time. Poor performance in binaural integration has been found to result in

difficulty in hearing in the presence of background noises or difficulty listening to two

conversations at the same time (Bellis, 1996). An individual with deficit in binaural integration

has been reported to have difficulty in integrating or processing information from more than one

source at a time.

Binaural integration and binaural separation tasks are considered warranted when deficits

are identified during dichotic evaluations. Musiek and Schochat (1998) used auditory training

which involved directing the stimuli to the stronger ear at a reduced level. This sound field

condition provided more cross-over between signals and greater demands on the patient than if

the task was conducted under earphones. It was suggested by Musiek et al. (2002) that this

procedure can also be modified using temporal offsets that lag in the poorer ear which improves

the poorer ear performance.

One form of remediation for individuals with binaural integration problems is dichotic

offset training, originally proposed by Rudmin and Katz (1982, cited in Katz et al., 1984). The

main objective of Dichotic Offset Training (DOT) was to train the child to differentially integrate

the two different stimuli which were separately given to both ears. Katz et al., (1984) studied 10

children aged 7-10 years who demonstrated difficulty on a dichotic test (SSW). They were given

DOT for 15 one-hour sessions using different offset conditions (500, 100, 300, 200, 100 and 0

msec). A consistent pattern of improvement was documented for Staggered Dichotic Digit Test

(SDD). However, they found a lack of statistically significant improvement on the SSW and

Speech-in-Noise tests. They suggested that a battery of auditory training tasks is likely to be

more beneficial than training any single skill.

Musiek and Schochat (1998) reported a case study of a 15 year old patient who

demonstrated bilateral mild deficits on dichotic digits test and moderate bilateral deficits on the

frequency pattern test and the compressed speech with reverberation test. A 6-week auditory

training program was given that included three 1-hour sessions per week along with home

training. Post auditory training performance showed higher scores on all central auditory tests.

A study by English et al., (2003) described another form of treatment for children with

deficit in dichotic learning skill. Ten children with reduced left ear Dichotic Digit Test (DDT)

scores (in the age range of 5 years 10 months to 10 years 9 months) were taken as subjects. They

received additional auditory training in conjunction with the left-ear-only stimulation. The


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training was given for 1 hour a week for 10 to 13 weeks. It was found that for most subjects

providing auditory stimulation to the left ear only improved left ear dichotic deficits as measured

by the dichotic digit test. From the above studies it is evident that different forms of training can

be provided which would result in an enhancement in dichotic performance. Both dichotic offset

training as well as stimulation of the deviant ear have shown to bring about improvement in

auditory integration.

According to Rupp and Stockdell (1978) 15 to 20% of school age population have some

type of language/learning disorder, 70 percent of these have some form of auditory impairment.

Further, Chermak and Musiek (1997) estimated that as many as 2 to 5% of the school age

population exhibit (C) APDs. In India it has been found that 3% of the children were found to

have dyslexia (Ramaa, 1985). Since many of the school going children have this problem there is

a need to find appropriate treatment procedures to help them develop their auditory skills and

perform better academically. Many intervention procedures have been reported in literature but

their efficacy has not been studied. Hence there is a need to study the effectiveness of an auditory

training procedure which would enhance auditory perception. The aim of the present study is to

determine the effectiveness of Dichotic Offset Training in children with low scores on the

Dichotic CV and the Dichotic Digit tests.

Method Participants

Two groups of participants were included in the present study, an experimental group and

a control group. All the participants who were in the age range of 7-12 years had studied in an

English medium school for at least 3 years. They had normal pure tone, immittance and speech

identification findings. Further, they had normal IQ and no speech problems. Only those who

failed the „Screening Checklist for Auditory Processing‟ (SCAP) developed by Yathiraj and

Mascarenhas (2002), the Dichotic CV test developed by Yathiraj (1999) and/or the Dichotic

Digit test developed at AIISH were included in the study. The participant selection criteria for

the control group were the same as the experimental group. While the experimental group

received dichotic offset training the control group did not.

Instrumentation

A calibrated dual channel audiometer (Orbiter 922) was utilized for pure tone testing and

for presenting the Dichotic CV and Dichotic Digit tests. To rule out any middle ear pathology a

calibrated immittance meter (GSI Tympstar) was used. An audio CD player (Philips) was used to

present test stimuli during evaluation while a portable audio CD player (Sony) with head phones

was used during the training sessions.

Test Environment

All the evaluations were carried out in a two room situation which was acoustically

treated as per ANSI (1991). Training was given in a quiet, distraction free environment.


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Material Used

To select the participants the „Screening Checklist for Auditory Processing‟ (SCAP)

developed by Yathiraj and Mascarenhas (2002) was used. Further, to determine their binaural

integration abilities they were evaluated utilizing the „Dichotic CV test‟ developed by Yathiraj

(1999) using the norms developed by Krishna (2001) and the „Dichotic Digit test‟ developed at

AIISH, with the norms obtained by Regishia (2003). The dichotic offset material developed by

Yathiraj (2006) was used for the training. It consisted of 12 dichotic word lists with six lists

having monosyllables without blends and six lists having monosyllables with blends. Each list

had 10 word pairs. The material had 6 offset lags (500 ms, 300 ms, 200 ms, 100 ms, 50 ms and 0

ms). Each offset lag consisted of 4 word lists, two having a right ear lag and two with a left ear

lag. Prior to administering the dichotic material the familiarity of the words was checked on ten

children in the age range of 7 to 7 years 11 months. In addition the intelligibility of the recorded

material which had been done on a computer by a female speaker with a sampling rate of 16

KHz was checked on ten adults. The material was found to be familiar to children as well as

intelligible to adults.

Procedure

Participant Selection Procedure

The initial selection of the participants was done by screening for children using the

„Screening Checklist for Auditory Processing‟ (SCAP), developed by Yathiraj and Mascarenhas

(2002). The checklist was administered by teachers who had a good knowledge about the

abilities of the children. Twelve of those children who had scored less than 50% were taken for

further evaluation. They were evaluated using dichotic CV and dichotic digit test. Half of the

participants were administered the Dichotic CV first while the other half the Dichotic Digit test.

Only those who failed these two tests were included in the study. The initial dichotic test scores

also served as the baseline evaluation.

Baseline Evaluation (Evaluation I)

The Dichotic CV test which consisted of 30 pairs of CV segments was administered at 50

dB HL. The children had to repeat the phonemes and the responses were written down by the

clinician. The scores obtained were compared with the norms developed by Krishna (2001). Of

the twelve children who were administered the test ten failed the Dichotic CV test.

The Dichotic Digit Test was presented at 40 dB SL. The children were instructed to

repeat all the numbers heard regardless of the order and the responses were written down. The

norms developed by Regishia (2003) were used to decide whether a child passed or failed a test.

Eleven out of the twelve children failed the test.

Dichotic Offset Training:

Six of the children who failed either of the above tests were given training using the

Dichotic Offset Training (DOT) material developed by Yathiraj (2006) using an audio CD player


141

with headphones. The training was started with the easier offset lag (500 ms) and once a child

obtained approximately 70% double correct scores the next lower lag material was used. If the

double correct scores obtained did not reach the 70% criteria the lists were presented again in a

randomized order. Gradually the offset lag was reduced and the task was made more difficult.

Each child was trained using all the lag times with both monosyllable lists without and with

blends. Throughout the training the children were provided feedback regarding their performance

(a head nod for every correct response). On completion of the 0 ms lag lists therapy was stopped.

The number of sessions required by the children varied between 10 to 15 sessions depending on

the abilities of the child.

Post therapy evaluation (Evaluation II)

After completion of the 0 ms lag therapy, post therapy evaluation was done for the

experimental group. For the control group evaluation II was done 15 days after evaluation I.

These evaluations were done using the dichotic CV and dichotic digit test and the single correct

and double correct scores were obtained. The scores obtained from evaluation I and II were

tabulated and scored.


A comparison of the scores obtained in I and II evaluations were done separately for the

experimental group and control group and also across groups. In addition a comparison of

dichotic offset scores obtained during therapy by the experimental group, was carried out.

I a) Comparison of evaluations I and II in the experimental group

The scores obtained by the experimental group during evaluation I (pre training

evaluation) and evaluation II (post training evaluation) on the dichotic tests were compared using

the Wilcoxon Signed ranks test. The results revealed a statistically significant difference between

the evaluation I and II scores following the dichotic offset training in the experimental group.

The test scores were statistically significant at 0.05 levels for both single correct and double

correct scores in the dichotic CV test. For the dichotic digit test, the scores were statistically

significant only for the right ear single correct scores at a 0.05 level of significance. The left

single correct scores and double correct scores did not show any statistically significant

improvement (Table 1 & Figure 1).

Table 1: Comparison of pre and post test scores in the experimental group

Test Score type Mean pre therapy score Mean post therapy score z value

Dichotic CV

Right single correct

Left single correct

Double correct

8.7

13.3

1.8

15.5

23.2

10.8

-2.201*

-2.01*

-2.207*

Dichotic digit Right single correct

Left single correct

Double correct

14.4

18.2

1.7

22.0

24.3

7.5

-2.201*

-1.577

-1.826

* Significant at 0.05 level


142

The results revealed that the dichotic offset training given to children who had deficit in

binaural integration was found to be effective in acquiring that particular auditory skill. The

improvement was found to be lesser in the Dichotic Digit test when compared to the Dichotic

CV test which may be because the Dichotic Digit test requires auditory memory skills also along

with binaural integration.

Experimental Group Control Group

05

1015202530

Sing

leRi

ght

Sing

leLe

ft

Dou

bleC

orre

ct

Sing

leRi

ght

Sing

leLe

ft

Dou

bleC

orre

ct

Score Type

Mea

n Sc

ores

Evaluation I

Evaluation II

Figure 1: Evaluation I and II for Dichotic CV test for the experimental & control Group

I b) Comparison of evaluations I and II done in the control group

The scores obtained by the control group during evaluations I and II were compared

using the Wilcoxon Signed rank test for both Dichotic CV and Dichotic Digit test. The results

revealed that there was not much improvement seen in the Dichotic CV and Dichotic Digit test

scores for the control group who did not receive any training. The Z scores obtained shows that

the difference in the scores was not statistically significant (Figure 2).

Experimental Group Control Group

0

5

10

15

20

25

30

Sing

leR

ight

Sing

leLe

ft

Dou

bleC

orre

ct

Sing

leR

ight

Sing

leLe

ft

Dou

bleC

orre

ct

Score Type

Mea

n Sc

ores

Evaluation I

Evaluation II

Figure 2: Evaluation I and II for the Dichotic Digit Test for experimental and control group

Thus it can be construed that without Dichotic Offset Training the individuals with poor

auditory integration skills do not show any marked variation in their performance. The finding of

the present study is similar to that of Katz et al., (1984) who also reported that children who did


143

not receive Dichotic Offset Training did not show an improvement in performance. Besides the

improvement seen using Dichotic Offset Training a study by English et al., (2003) showed that

even training those with poor dichotic scores in one ear resulted in improvement in dichotic

scores. In their study the poorer ear was stimulated and improvement was seen in left ear alone.

II) Comparison of evaluation I and II across groups

The scores obtained were compared between the experimental and control groups,

separately for evaluations I and II (Table 2). For evaluation I the mean scores for both the groups

did not vary much for the Dichotic CV and the Dichotic Digit test. However, for evaluation II,

there were variations in the mean scores for the Dichotic CV test but not much for the Dichotic

Digit Test.

To compare the mean scores between the experimental and control groups for evaluations

I and II, non-parametric Mann-Whitney test was carried out. From Table 3 it is evident that there

was no significant difference between the experimental and control group for evaluation I in the

Dichotic CV and the Dichotic Digit Test. However in evaluation II there was a statistically

significant difference across the groups in the Dichotic CV test. The left single correct score

showed a significant difference at the 0.05 level whereas the right single correct score and double

correct score showed a significant difference at 0.1 level.

Table 2: Mean and standard deviation scores for both the groups on I and II evaluations

Evaluation

Test

Score Type Experimental group Control group

Mean SD Mean SD

Evaluation I

Dichotic CV

RE 8.7 4.5 9.6 3.9

LE 13.3 7.7 16.3 6.6

DC 1.9 3.6 2.3 4.8

Dichotic digit test

RE 14.4 5.0 17.1 4.7

LE 18.2 10.2 23.3 4.9

DC 1.7 2.4 4.8 8.7

Evaluation II

Dichotic CV

RE 15.5 3.3 12.5 2.3

LE 23.2 2.7 18.2 4.5

DC 10.8 5.0 4.7 4.4

Dichotic digit test

RE 22.0 3.2 18.4 4.5

LE 24.3 4.3 24.1 5.9

DC 7.5 8.4 6.5 7.3

The Dichotic Digit test did not show any significant difference when compared across the

groups. Thus it can be concluded that following training the experimental group showed a

significant difference which was not observed in the control group on a test that purely tapped

auditory integration (dichotic CV). In contrast, the test that tapped both auditory integration and

auditory memory (dichotic digit test) did not show such an improvement.


144

Table 3: Comparison of mean scores across the groups

Test Group Score

Type

Evaluation I

Mean scores

Significance Evaluation II

Mean scores

Significance

Dichotic CV

Experimental RE 8.666 NS

15.500 0.124**

Control RE 9.583 12.500

Experimental LE 13.333 NS

23.166 0.036*

Control LE 16.333 18.166

Experimental DC 1.833 NS

10.833 0.091**

Control DC 2.333 4.666

Dichotic

Digit Test

Experimental RE 14.416 NS

22.000 NS

Control RE 17.083 18.416

Experimental LE 18.166 NS

24.250 NS

Control LE 23.250 24.083

Experimental DC 1.666 NS 7.500 NS

Control DC 4.833 6.500

* Significant at 0.05 level; ** Significant at 0.1 level

III) Comparison of dichotic offset scores in the experimental group:

The scores obtained by the experimental group during the dichotic offset training were

also analyzed. The scores obtained at each of the lag times for the monosyllables without blends

(Figure 3) and with blends (Figure 4) were analyzed. The double correct scores obtained during

the therapy sessions were compared across various offset lags. This was done separately for the

training material having a right lag and that having a left lag. For each of the conditions the

baseline scores obtained at the start of the training were compared with the scores obtained at the

end of the training for a particular lag time.

Figure 3: Double correct scores for monosyllables without blends, for varying lag times


145

Figure 4: Double correct scores for monosyllables with blends, for varying lag times

From Figures 3 and 4 it can be observed that for all the lag conditions, material type

(non-blends and blends) and ear of lag, there was an improvement in performance with training.

The improvement seen during therapy was greater for the monosyllables without blends than for

the monosyllables with blends. The Mann-Whitney test was carried out to check for overall

changes between the baseline performance and the post therapy scores for each lag time. A

statistically significant response was observed only for the 100 msec lag time. For other lag

times, though there was an improvement, it was not statistically significant.

Conclusion

Based on the results of the present study it can be concluded that the Dichotic Offset

training (DOT) is found to be effective in helping the children with deficits in binaural

integration. No significant improvement was found for the control group in both the Dichotic CV

and Dichotic Digit tests. The experimental group showed significant improvement (p < 0.05) in

both the single and double correct scores in the Dichotic CV test following training. In the

Dichotic Digit test the significant improvement was found only for right ear single correct score

(p < 0.05) and not for left ear single correct and double correct score. It can be concluded that the

improvement is more for a dichotic test that taps only binaural integration and not a test that taps

both binaural integration and auditory memory.

References

ANSI. Maximum permissible ambient noise levels for audiometric test rooms, ANSI S3.1. New

York: American National Standards Institute (ANSI), 1991.

ASHA (2005). (Central) auditory processing disorders (Technical report). Available at

www.asha.org /members/deskref-journals/deskref/default.


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Bellis, T.J., (1996). Assessment and Management of Central Auditory Processing Disorders in

the Educational Setting: From Science to Practice. San Diego, CA: Singular.

Chermak, G.D. & Musiek, F.E., (1997). Central Auditory Processing Disorders: New

Perspectives. San Diego, CA: Singular.

Chermak, G.D. & Musiek, F.E., (2002). Auditory Training: Principles and Approaches for

Remediating and Managing Auditory Processing Disorders. Seminars in Hearing, 23(4),

297-308.

English, K., Martonik, J. & Moir, L. (2003). An auditory training technique to improve

dichotic listening, Hearing Journal, 56(1), 34-38.

Hanson, D.G. & Ulvestad, R.F., (1979). Otitis media and child development. Annals of Otology,

Rhinology and Laryngology, 88 (Suppl.60), 1-111.

Katz, J., Chertoff, M. & Sawusch, J., (1984). Dichotic training. Journal of Auditory Research,

24, 251-264.

Krishna, G. (2001). Dichotic CV tests – Revised: Normative Data on Children, Independent

project done as part fulfillment for the Degree of Master of Science, Submitted to the

University of Mysore, Mysore.

Musiek, F.E. & Schochat, E., (1998). Auditory training and central auditory processing

disorders: A case study. Seminars in Hearing, 19, 357-366.

Musiek, F. E., Shinn, J. & Hare, C., (2002). Plasticity, Auditory Training, and Auditory

Processing Disorders. Seminars in Hearing, 23(4), 263-275. Guest Editor: Chermak,

G.D.

Putter-Katz, H., Said, L.A., Feldman, I., Meran, D., Kushmit, D., Muchnik, C. & Hildesheimer,

M., (2002). Treatment and evaluation indices of Auditory Processing Disorders. Seminars

in Hearing, 23(4): 357-363.

Ramaa, S., (1985). Diagnosis and remediation of dyslexia. Ph.D. Thesis, University of Mysore,

Mysore.

Regishia, A., (2003). Effect of maturation on Dichotic tests: A comparison of Dichotic Digit and

Dichotic Consonant Vowel test, Independent project done as part fulfillment for the

Degree of Master of Science, Submitted to the University of Mysore, Mysore.

Rupp, R.R. & Stockdell, K.G., (1978). Speech protocols in Audiology. New York: Grune &

Stratton.

Yathiraj, A., (1999). The Dichotic CV Test. Unpublished Material developed at the Department

of Audiology, AIISH, Mysore.

Yathiraj, A. & Mascarenhas, K. (2002). Effect of Auditory stimulation of central auditory

processes in children with APD. A project funded by the AIISH research fund.

Yathiraj, A., (2006). The Dichotic Offset Training Material. Unpublished Material developed at

the Department of Audiology, AIISH, Mysore.


147

Development of High And Low Predictable English

Sentence Test (EHLPS)

V V Rahana Nandan & Asha Yathiraj

Abstract

In an everyday situation there is a combination of high and low predictable sentences.

The present study aimed at developing an English High Predictable-Low Predictable Sentence

test for Non-Native English speakers (EHLPS). The test was administered on twenty normal

hearing and eleven individuals with mild-to-moderate sensorineural hearing loss. The responses

were scored in terms of high and low predictable target words and key words in the sentences.

The statistical analysis of the data revealed that there was a significant difference between the

normal group and individuals with hearing impairment on the EHLPS for both key word and

target word scoring. The developed test has been found to be useful in determining the

perceptual problems in individuals having hearing loss. Hence it may be used as a part of

diagnostic test battery and for pre and post therapy evaluations in individuals having auditory

perceptual problems.

Key words: speech identification, perceptual problems, sensorineural hearing loss

Introduction

Speech is highly redundant because the information in it is conveyed in several ways

simultaneously (Martin, 1994). A hearing loss involving only part of the auditory frequency

range may go undetected in a speech test which is not carefully controlled. It has been noted by

Martin (1994) that it was not possible in a single test to sample all types of speech events that

might occur in practice. This is because everyday speech communication covers a wide range of

spoken material and takes place in a variety of contexts.

Denes and Pinson (1963) reported that basically two kinds of operations were involved in

the understanding of sentences. One was the reception and initial processing of acoustic

information through the auditory system and the other was the utilization of linguistic

information that is stored in memory. A test of a listener‟s ability to understand everyday speech

therefore must assess both the acoustic-phonetic and the linguistic-situational components of the

process.

The goal of most speech perception tests is to provide a measure of an individual‟s

performance in everyday listening situations. Although there are many meaningful word and

nonsense syllable tests available that provides analytic information regarding a patient‟s speech

perception abilities, sentence tests offer additional insight about the individual‟s performance in




148

more realistic communication situations. Sentences are considered more valid indicators of

intelligibility and a better representation of spoken communication. The use of single words,

especially single syllable words, imposes severe limitations on the capacity to manipulate certain

patterns like intonation and co-articulation effects on the ongoing speech. Sentences have face

validity as „natural‟ and „meaningful‟ stimuli for assessing auditory function (Miller, Heise &

Lichten, 1951).

Different forms of sentence tests have been developed over the years. Certain sentence

tests have been developed with the aim of tapping the perceptual difficulties of those with

hearing loss (Mendel & Danhauer, 1997). Other sentence tests have been constructed to

determine difficulties in the perception of high predictable or low predictable sentences. High

predictable sentences are those in which the target test words can be guessed from the context

whereas in low predictable sentences the final word cannot be guessed from the sentence context

(Kalikow, Stevens & Elliot, 1977). In our day-to-day life situation there is a combination of high

and low predictable sentences.

The present study aimed to develop a test having low and high predictability sentences

and administer it on a group of normal hearing individuals and a group having mild-to-moderate

hearing loss. It would be determined whether the test can differentiate the perceptual problems of

individuals with a hearing loss.

Method

Participants: The study was done in the three stages. The participants in each stage were

different. In stage I, ten normal hearing children in the age range of 12 years to 17 years 11

months were used to check for the familiarity of words used in the sentence test. In addition to

classify the sentences as high predictable and low predictable 10 normal hearing adults (18 to 30

years) were used. For stage II of the study two groups of normal hearing individuals were used

each consisting of 20 members. One group was in the age range of 12 years to 17 years 11

months and the other in the age range of 18 years to 30 years. In stage III ten individuals having

mild-to-moderate sensorineural hearing loss were taken to check the utility of the material.

Each participant for stages I and II had English as a medium of instruction for at least 5

years. They had normal hearing (i.e. air conduction and bone conduction thresholds within 15 dB

HL with an air-bone gap of less than 10 dB in the frequency range of 250 Hz to 8 KHz and 250

Hz to 4 KHz respectively). The participants had normal speech and language with no history of

hearing loss and any report of neurological problems. The participant inclusion criterion for stage

III was the same as that of stages I and II except that they had a mild-to-moderate sensorineural

hearing loss. Their age ranged from 20 to 55 years (mean age of 40 years).

Instrumentation: A dual channel calibrated diagnostic audiometer (Madsen OB 922) was used

for establishing hearing thresholds and for administering the developed test material. To rule out

middle ear problems an immittance audiometer (GSI-Tymstar) was utilized. A Pentium IV


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computer with the WavePad software was used to record the material and normalization of the

speech material was done using the Adobe Audition software.

Test development: Seventy-five sentences were constructed with each sentence containing 5 to

7 words. A pilot study was done to check for the familiarity of the developed material and to

classify them as high and low predictable sentences. Ten normal hearing children aged 12 years

were used to check the familiarity of words. The participants were instructed to classify the

words on a three point scale as „highly familiar‟, „familiar‟ or „not familiar‟. The familiarity of

words was decided based on their frequency of occurrence in regular communication.

To classify the sentences in terms of predictability ten adults were used. The adults were

instructed to categorize the sentences as high predictable or low predictable sentences based on

their ability to guess the final word. Each participant was given the set of sentences with the

target word not provided and they had to guess it. They were instructed to give as many options

as possible for the target word. The sentences in which only one option was given that matched

the test stimuli were classified as highly predictable sentences. In contrast, sentences with more

than one target word were considered as low predictable sentences. Using the above material five

lists of sentences was developed. Each of them consisted of 10 sentences. The sentences were

such that they contained equal number of high and low predictable sentences (Appendix A). The

developed test was titled „High predictable and low predictable English sentence test for non-

native English speakers (EHLPS).

A female speaker was used for recording the material onto a computer. The „WavePad‟

software was used for the recording. The recording was done in a quiet room using a sampling

rate of 16 KHz. Scaling of the signals were done using „Adobe Audition‟ software to ensure that

the intensity of all the sounds were equal. A 1 KHz calibration tone was recorded prior to each

list.

Procedure: Administration of the developed sentence test was done on normal hearing

individuals in stage II in a sound treated double suite. Prior to the administration of the test the

pure tone thresholds of the participants were obtained. The speech recognition threshold (SRT)

was established using the English paired words developed by Chandrashekara (1972). The

recorded version of the EHLPS test was played on a Pentium IV computer using the WavePad

software. The output of the computer was routed to the tape input of the audiometer. The output

from the audiometer was played at 40 dB SL with reference to the participant‟s SRT. The

calibration tone was used to adjust the VU meter deflection of the audiometer to zero. The

participants heard the recorded material through headphones. Half the participants were tested in

the left ear and half in the right ear to avoid any ear effect. The participants were asked to write

down as well as verbally repeat what they heard.The verbal responses were noted by the

experimenter. The procedure for stage III was similar to that of stage II. Instead of evaluating

normal hearing individuals the test was administered on ten adults with a mild-to-moderate

hearing loss. They were tested in their better ear.


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The responses from the participants were scored in two different ways. While the first

way involved scoring the high predictable or low predicable target words (final words) the

second way involved scoring the key words in the sentences. Every correct score was awarded a

score of one and every incorrect response got a score of zero. The maximum score for target

words was ten for each list with five being awarded for the high predictable sentences and the

other five for the low predictable sentences. In contrast the scores for the key words varied

across each list. List 1 had 28 key words while lists 2, 3, 4 and 5 had 29, 27, 30 and 27 key words

respectively. The raw scores for target words and key words of the participants were statistically

analyzed separately using the computer software SPSS (version 10.0).


The data obtained on the group having normal hearing and the group having hearing loss

were analysed separately. For each of the groups the analyses were done within lists and across

lists.

Analyses of data from Nnormal hearing individuals

To compare the scores of high and low predictable sentences within each list descriptive

statistics was initially done where the mean, standard deviation (SD) and 95% confidence

interval were calculated. This was done separately for each of the lists (Table 1). It can be

observed from the table that for both high predictable (HP) and low predictable (LP) sentences

the mean scores were either equal to the maximum scores or were just slightly less than the

maximum scores. The variability in scores was almost nil or minimal as evident from the SD

values.

Table 1: Mean, SD and 95% confidence interval values for High predictable (HP) and Low

predictable (LP) sentence scores

List

no

Sentence

type

Mean

(Max score=5) SD

Lower

bound

Upper

bound Significance

List 1 HP 4.85 .37 4.68 5.00

NS LP 5.00 .00 - -

List 2 HP 5.00 .00 - -

NS LP 4.85 .49 4.62 5.00

List 3 HP 4.95 .22 4.85 5.00

NS LP 5.00 .00 - -

List 4 HP 5.00 .00 - -

NS LP 4.85 .37 4.68 5.00

List 5 HP 5.00 .00 - -

NS LP 4.9 .45 4.69 5.00

Note. NS = Not significant

Further to check for the variation between the high and low predictable sentences within

each list paired sample t-test was done. The t values obtained showed no significant difference at

the 0.05 level (Table 1). The findings of the present study are not in agreement with that of


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Kallikow, Stevens and Elliot (1977). They reported that better performance was noted for HP

sentences than the LP sentences. This lack of agreement in finding can be attributed to the

difference in testing procedure. The study by Kallikow et al. was done in presence of various

signal-to-noise ratios (SNR) whereas the EHLPS was done in a quiet condition. Individuals with

normal hearing depended more on the contextual cues in adverse listening conditions such as

noise and not in a quiet condition. Had the present study been conducted in the presence of noise

a similar result would have been probably obtained as that of Kallikow et al.

To check the difference between high predictable and low predictable sentence scores

across lists a one-way repeated measure ANOVA was carried out. It showed no significant

difference across the lists between the high predictable sentences [F (4, 76) = 2.259, p > 0.05]

and low predictable sentences [F (4, 76) = 1.048, p > 0.05]. The above findings indicate that all

five lists are similar in terms of HP and LP sentences. Since normal hearing individuals

performed equally well on all five tests, any one of them can be used while evaluating the speech

identification ability of clients when HP-LP scoring is done. Repeated measures ANOVA was

also calculated for key word scores across sentences and it showed a significant difference [F (4,

76) = 3.009, p < 0.05]. This was unlike that seen for the HP-LP target word scores (Table 1)

where there was no significant difference across lists. This highlights that the lists are equal

when they are valued in terms of HP and LP scores but are unequal when they are scored on the

basis of key words. The mean values for both the target HP-LP scoring and key word scoring is

given in Table 2. Within each list the scores for HP-LP words and key words are comparable.

Table 2: Mean values for HP-LP target word scores and key-word scores

List no HP-LP Target word score Key word score

List 1 9.85 (98.5%) 27.6(97.6%)

List 2 9.85 (98.5%) 28.6 (98.7%)

List 3 9.95 (99.5%) 26.9 (99.6%)

List 4 9.85 (98.5%) 29.7 (99.3%)

List 5 9.9 (99%) 26.6 (98.7%)

Note: Value given in bracket refers to the percentage score. Maximum HP-LP target word scores

was ten and maximum key word score ranged between 27-30.

From the Bonferroni‟s multiple comparison test it was evident that List 1 and List 3

showed a significant difference while the other pairs of lists did not. The participants obtained

significantly lower scores on List 3 when compared to List 1.

A possible reason as to why List 1 and List 3 are not equal could be due to the method

used in the construction of the lists. While constructing the test care was taken to equate the

target HP-LP words in each sentence in terms of frequency of occurrence of various phonemes.


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This was not done for the key words as the main aim of the study was to develop and evaluate

HP-LP sentences. Further it is possible that the HP-LP target words were easier to predict in the

sentence compared to the other key words in the sentences. Also the words occurring toward the

end of a sentence tend to be more predictable and more likely to be restored and recalled quickly

than the rest of the words in the sentence.

Thus, it is recommended that when key words are being used to score the responses of

participants the combination of List 1 and 3 should not be used for comparing perceptual

outcomes. However, other list combinations can be used for perceptual evaluation of individuals.

These combinations include Lists 1, 2, 4 and 5 or Lists 2, 3, 4 and 5.

Analyses of data collected from the group with hearing impairment

Table 3: Mean, Standard deviation and 95% confidence interval values for HP and LP sentence

scores in individuals with hearing impairment

List no Mean

(Max score = 5) SD

Lower

bound

Upper

bound

Level

of Sig.

List 1 HP 3.55 1.21 2.73 4.36

0.831 LP 3.45 .93 2.83 4.08

List 2 HP 4.55 .69 4.08 5.00

0.006** LP 3.45 .93 2.83 4.08

List 3 HP 4.64 .50 4.30 4.98

0.019* LP 3.55 1.29 2.68 4.41

List 4 HP 4.55 .52 4.19 4.90

0.000** LP 3.18 .75 2.65 3.69

List 5 HP 4.64 .50 4.30 4.98

0.038* LP 3.91 1.14 3.15 4.67

Note. * Significant at .05 level; ** Significant at .01 level

High and low predictable sentence scores within each list were compared in the

individuals with hearing impairment. The mean scores varied only minimally depending on

whether the sentence was a high predictable one or a low predictable one. For all five lists, the

scores obtained on the LP sentences were lower. The t-test revealed a significant difference

between the HP and LP sentences for all but List 1 either at the 0.05 level or the 0.01 level

(Table 3). Also, the variability in scores was comparatively more in LP sentences compared to

the HP sentences as seen from the SD values.

The findings of the present study reveal that the individuals with hearing impairment did

depend more on the contextual cues rather than the audibility cues. The contextual cues were

limited in the LP sentences and hence they obtained comparatively less scores in these sentences.

One-way repeated measure ANOVA was done to compare the difference between high

predictable and low predictable sentence scores across lists. The scores obtained from the

individuals with hearing impairment showed a significant difference between the lists for the

high predictable sentences [F (4, 40) = 4.518, p < 0.05]. The Bonferroni‟s multiple comparisons


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test revealed that List 1 and List 2 had a significant difference and the other pairs of lists did not

show a significant difference. The results were not similar for the low predictable sentences

across lists. Here there was no significant difference seen [F (4, 40 = 0.974, p > 0.05] indicating

that individuals with hearing impairment performed similarly on the LP sentence across lists.

Probably with the HP sentences the individuals were able to guess the target word in certain lists

and not so in certain other lists. However, this was not the case with the LP sentences.

The mean scores obtained for HP-LP target words and key words, expressed in terms of

raw scores as well as percentage, are depicted in Table 4. When the key words were scored in

individuals with hearing impairment it showed a significant difference across lists [F (4, 40) =

4.905, p < 0.05]. This is similar to what was observed for the LP sentence scores in the group

with hearing impairment. It was seen from the Bonferroni‟s multiple comparison test that for the

key word scores, List 2 and 5 showed a significant difference. Likewise Lists 3 and 5 had a

significant difference while the other lists did not have a significant difference between them.

Table 4: Mean and SD for HP-LP target word scores and key word scores in individuals with a HI

List no Target HP-LP

word score

Key word

score

List 1 7

(70%)

20.09

(71.7%)

List 2 8

(80%)

21.81

(75.1%)

List 3 8.19

(81.9%)

20.36

(74.7%)

List 4 7.73

(77.3%)

23.36

(79.3%)

List 5 8.55

(85.5%)

22.81

(85.1%)

Note: Value given in bracket refers to the percentage score; Maximum HP-LP word scores was

ten and Maximum key word score ranged between 27-30

Scores were comparable within a list when HP-LP target words and key words scores

were used. The similarity in scores was more pronounced in List 1, 4 and 5. Both scoring

procedures seem to detect the perceptual problems of individuals with hearing impairment.

Comparison between Normal Group and the Deviant Group

The high and low predictability sentence scores were compared between groups. The

mean HP-LP scores for the two groups are depicted in Table 5. The mean scores obtained by the

individuals with hearing impairment were lower when compared to the normal hearing group.

An independent t-test was performed and it was found that there was a significant difference at

the 0.01 level between the two groups for all the Lists for both HP and LP sentences. Only the

HP sentences in List 3 were significantly different at the 0.05 level. The findings of the present

study are in agreement with that reported in literature. Olsen, Noffsinger and Kurdziel (1975)

have documented that speech discrimination scores were comparatively worse in individuals


154

with hearing impairment in quiet. Similarly, Pekkarinen, Salmivalli and Suonpaa (1990) reported

that word recognition scores were poorer in their participants with hearing impairment compared

to the normal hearing group in a quiet situation. Thus it can be inferred that HP-LP target word

scores are sensitive in assessing perceptual problems in individuals with hearing impairment.

Both high predictable sentences as well as low predictable sentences are equally sensitive.

Table 5: Mean and t values for HP-LP target words across normal and individuals with HI

List Sentence type Groups Mean (Max score = 5) T values

List 1

HP Normal 4.85

4.50** HI 3.55

LP Normal 5.00

7.50** HI 3.45

List 2

HP Normal 5.00

2.99** HI 4.55

LP Normal 4.85

5.49** HI 3,45

List 3

HP Normal 4.95

2.40* HI 4.64

LP Normal 5.00

5.10** HI 3.55

List 4

HP Normal 5.00

3.94** HI 4.55

LP Normal 4.85

8.36** HI 3.18

List 5

HP Normal 5.00

3.27** HI 4.64

LP Normal 4.90

3.47** HI 3.91

One-way repeated measure ANOVA was calculated for the key words in the normal and

deviant group and it showed a significance difference [F (4, 116) = 9.067, p < 0.05]. Along with

ANOVA independent t-test was also done to check for difference between key word scoring

across both the groups. The t values showed a significant difference at the 0.01 level (Table 6).

This shows that key word scoring is also an equally sensitive test procedure to detect perceptual

deficits in the hearing impaired population.

Table 6: Mean and t values for key words across normal and HI group

List no Groups Mean T values

List 1 Normal 97.66

9.90** HI 71.75

List 2 Normal 98.78

8.52** HI 75.19

List 3 Normal 99.63

9.36** HI 74.74

List 4 Normal 99.33

6.80** HI 79.36

List 5 Normal 98.70

6.41** HI 85.10

Note. ** Significant at .01 level


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Conclusion Thus from the present study it can be concluded that there is no significant difference

between the high predictable and low predictable sentence scores in the normal population. It is

seen that all the five lists containing high predictable and low predictable sentences were equal

but the lists are unequal when key words are scored in normal hearing individuals. In individuals

with hearing impairment the LP sentences yielded significantly lower scores than the HP

sentences for most of the lists. Overall there was a significant difference between the normal

hearing group and individuals with hearing impairment on the EHLPS for both key word and

target word scoring. Thus EHLPS is a sensitive test for the assessment of auditory perceptual

difficulty in individuals having a hearing problem. The test would provide information about the

auditory perceptual problems present in individuals having a hearing loss.

References

Chandrashekara, S. (1972). Development and standardization of speech test material in English

for Indians. Unpublished Master‟s Dissertation, University of Mysore, Mysore.

Denes, P. B. & Pinson, E. N. (1963). The Speech Chain. Baltimore. Waverly Press Inc.

Kalikow, D. N., Stevens, K. N. & Elliott, L. L. (1977). Development of a test of speech

intelligibility in noise using sentence materials with controlled word predictability.

Journal of Acoustical Society of America. 61, 1337-1351.

Martin, F.N. (1994). Introduction to Audiology. (Eds.), New Jersey Prentice Hall, Englewood.

Cliffs.

Mendel, L. L. & Danhauer, J. L., (1997). Audiological evaluation and management and speech

perception assessment. San Diego. London. Singular Publishing Group Inc.

Miller, G. A., Heise, G. A. & Litchen, W. (1951). The intelligibility of speech as a function of

the context of the test materials. Journal of Experimental Psychology, 41, 329-335.

Olsen, W, O., Noffsinger, D. & Kurdziel, S. (1975). Speech discrimination in quiet and in white

noise by patients with peripheral and central lesions. Acta Otolaryngol, 80, 375-382.

Pekkarinen, E., Salmivalli, A. & Suonpaa. J. (1990). Effect of noise on word discrimination by

participants with impaired hearing, compared with those with normal hearing. Scand

Audiol, 19, 31-36.

Appendix – A

English High Predictable Low Predictable Sentence test for Non-native English speakers

(EHLPS)

List 1

1. A year has twelve months.

2. I hit the ball with a bat.

3. The sport shirt has short sleeves.

4. I was made to lift my bag.


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5. The baby slept with closed eyes.

6. She baked his birthday cake.

7. The room is always kept neat.

8. Put a battery in the clock.

9. February has 28 days.

10. He looks different with a beard.

List 2

1. She just heard a loud scream.

2. The peacock is our national bird.

3. He had a bath with hot water.

4. The heavy rains caused a flood.

5. The baby has chubby cheeks.

6. I have got a new dress.

7. He wiped the mirror with a sponge.

8. He eats using his right hand.

9. A day has 24 hours.

10. Give her a few slices of bread.

List 3

1. The dogs were tied to the gate.

2. She has to pay the tuition fees.

3. We got drenched in the rain.

4. I need to fill ink in my pen.

5. He prefers to have tea.

6. I got stuck in the lift

7. Lotus is our national flower

8. The bomb exploded with a blast.

9. The barber cut his hair.

10. She opened the room with a key.

List 4

1. The cricket match ended in a draw.

2. The bomb exploded with a blast.

3. He stuck the paper with glue.

4. In autumn, the trees shed their leaves.

5. Sunday is a holiday.

6. Every morning I brush my teeth.

7. There are 7 days in a week.

8. She hit the water with a splash.

9. He was asked to unlock the door.

10. We could consider the request.

List 5


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1. A dog has four legs.

2. He was assigned the task.

3. A rainbow has seven colours.

4. I met with a car accident.

5. The sun rises in the east.

6. The door was wide open.

7. I made the call from a booth.

8. Stop playing with your hands.

9. Help me in arranging the books.

10. We should have considered the matter.

Note: Words in bold are the key words and words underlined are the HP-LP target words.


158

NRT: Comparison of Artefact Cancellation and

Threshold Estimation Techniques

Shibasis Chowdhury & P Manjula

Abstract

Neural response telemetry (NRT) is a process of recording electrically evoked compound

action potential (ECAP) from the auditory nerve in individuals with cochlear implants. Since

ECAP is a very early potential, there is an adverse effect of stimulus artefact on the recording of

the ECAP via NRT. Several approaches have been proposed to reduce the stimulus artefact in

NRT. A comparison of three such techniques for artefact reduction was made. Results revealed

that all the techniques can be used to record NRT. A comparison of techniques available to

determine the threshold NRT (T-NRT) was also done and results revealed that the visual

estimation of T-NRT was a better choice.

Key words: Alternating polarity, forward masking, artefact template, visual estimation, peak

picker.

Introduction

The most direct measure of auditory nerve activity in cochlear implant users is the

electrically evoked compound action potential (Abbas et al., 1999). The first recording of

electrically evoked whole nerve compound action potential (ECAP) from human cochlear

implant users was reported by Brown, Abbas and Gantz in 1990. The method used was an

adaptation of the paradigm described by Sauvage, Cazals, Erre, and Aran in1983. The term

“Telemetry” describes the measurement of data and transmission of data from a remote source to

a receiving station for recording and analysis (Mens, 2004). The telemetry system used to

measure the ECAP in Nucleus cochlear implant users is referred to as NRT (Abbas et al., 1999).

In humans this response consists primarily of a negative peak often referred to as N1 with a

latency of 0.2 to 0.5 ms; and at high presentation levels, the initial negative peak is often

followed by a less robust positive peak that is referred to as P2 (Brown, 2004).

While recording ECAP the problem faced is that, in addition to the neural response

evoked by the electrical stimulus pulse, a very large stimulus artefact will also be recorded which

is often large to saturate the recording amplifier (Brown, 2004). As a result the ECAP could not

be visualized in the presence of the artefact. This problem has led to several proposals for

reducing or minimizing the stimulus artefact recorded during ECAP measurement.

For recording NRT there are several techniques available in the Custom Sound EP

software (version 1.3) for artefact reduction such as 1. Forward masking, 2. Artefact template, 3.


email: [email protected]


159

Alternating polarity and 4. Masked response extraction. These techniques are referred to as

artefact cancellation techniques in NRT. The present study is concerned with only the first three

artefact cancellation techniques. Once the NRT is recorded at different current levels there is a

need to identify the threshold of NRT (T-NRT), i.e., the minimum current level at which a NRT

response is obtained. Threshold estimation of NRT can be done by visual detection of the NRT

waveform or automatically by the software, based on some predefined rules.

The Custom Sound EP software has the option of „peak picker‟ which offers the facility

of automated NRT response identification. Threshold can be defined as the lowest current level,

at which the peak picker identifies a NRT response. Also, there is an option for extrapolated

NRT threshold identification using regression analysis. In the present study, the different artefact

cancellation techniques (forward masking, artefact template and alternate polarity) and the

different threshold estimation techniques (visual T-NRT estimation, peak picker based T-NRT

estimation and regression analysis extrapolated T-NRT) were compared across. The different

artefact cancellation and threshold estimation techniques are described briefly below.

Forward Masking

The method involves a non-simultaneous forward masking paradigm, using a masker plus

probe condition, to put the auditory nerve fibers into refractory period and thereby recording

only the stimulus and masker artefact. This is subtracted from the probe alone condition which

consists of both stimulus artefact and neural response. The resultant is a neural response with a

masker artefact. The masker artefact is then removed by recording of a masker alone condition.

Once the recordings have been made in each of these three stimulation conditions, extraction of

the ECAP from the stimulus artefact is accomplished in two steps. First, the average response

recorded in the second condition (masker plus probe) is subtracted from the averaged response

recorded in the first condition (probe alone). This subtraction yields a response in which the

masker artefact has been inverted 180 degrees and the probe artefact has been minimized. The

second step is to add the response recorded in the third condition (masker alone) to the product

of the subtraction. This step allows elimination, or at least reduction, of the artefact associated

with the masker. The main assumptions is that the masker-probe interval is short enough (<0.5

ms) for all the nerves to be in their absolute refractory state (Brown & Abbas, 1990). If the

masker-probe interval is > 0.5 ms, there may be a relative refractory component at the moment of

the probe stimulus in the masker-probe frame, caused by some of the nerves that have recovered

from their refractory state (Klop, Hartlooper, Briare & Frijns, 2004). This will result in unwanted

neural response to this probe, which influences the final response calculated.

Artefact Template

A second technique for reducing the effects of stimulus artefact is template subtraction

(Miller, Abbas, Rubinstein, Robinson, Matsuoka & Woodworgh, 1998). The principle that the

tissue impedance and the amplifier are linear, and a current that is twice as high will produce an

artefact that is twice as large is used to record a scaled version of the artefact by measuring the


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artefact at a low, sub-threshold current level where there is no response and only contain artefact.

The artefact template can be scaled up accordingly at a higher supra threshold stimulation level.

The measured trace minus the scaled up artefact template should result in a pure neural response.

Alternating Polarity

Another common technique by which the stimulus artefact contamination can be

minimized is by alternating the polarity of the stimulus in successive presentations and then

averaging the response that is recorded. The artefact recorded is out of phase for the anodic-

leading and cathodic-leading biphasic current stimuli. When averaging is done the out of phase

stimuli artefact are averaged out. The neural response evoked by the stimulus should not reverse

the polarity as the stimulus polarity is changed and therefore will be preserved in the average

(Brown, 2004). Brown, Abbas and Gantz (1990) reported successful recording of NRT using

alternating polarity.

Visual T-NRT estimation

In this approach a visual observation of the NRT recordings and determination of the

lowest current level of the stimulus that elicits a measurable response is noted as T-NRT. This

can be used either through ascending or descending approach. Ideally initial responses should be

obtained at a high enough supra threshold level so that the user can be sure that the neural

response decreases with amplitude. One drawback to the visual detection method is that for

systems with a relatively high noise floor the true threshold can be obscured by the noise,

yielding a threshold estimate that is likely to be too high (Hughes, 2006).

Peak picker based T-NRT estimation

The second option to determine T-NRT is the peak picker. The peak picker identifies the

N1 and P2 of the NRT waveforms based on a set of rules that are dependent on a set of

parameters such as signal to noise ratio, current level, correlation of the recording with the

previous current level and correlation of the recording with a known response. These set of rules

constitute the peak picker algorithm. The T-NRT can be defined as the lowest current level at

which the peak picker identifies a NRT response.

Regression analysis extrapolated T-NRT

The third method of threshold estimation in NRT involves applying a regression analysis

to points on an input-output (or amplitude growth) function. Threshold is determined as the level

at which the regression line crosses zero amplitude (i.e., intercept of the x-axis where y = 0). The

advantage to this method is that lower thresholds can be extrapolated for high-noise systems

(Hughes, 2006).

Since there are differences in the working principle of the three different artefact

cancellation techniques mentioned above it can be possible that the NRT or the ECAP recorded

using them might be expected to vary in terms of latency, threshold, amplitude and morphology.

Therefore the need arises to study systematically, in detail and compare the NRT recorded using


161

the three different artefact cancellation techniques mentioned. There is a dearth of literature

comparing various techniques to reduce artefact while recording NRT/ECAP.

Further comparing the threshold and the amplitude at the threshold of the recorded

NRT/ECAP using different techniques to reduce stimulus artefact is also required. With respect

to the threshold estimation techniques, the efficacy of the peak picker and the regression analysis

in order to extrapolate threshold of NRT or T-NRT, with the NRT recorded using the three

different artefact cancellation techniques needs to be studied. These methods of estimation of T-

NRT need to be compared to that of obtained by the visual method of NRT estimation.

The relationship between T-NRT and behavioral thresholds have been used to program

the speech processors of the cochlear implant (Brown, Hughes, Luk, Abbas, Wolaver & Gervais,

2000; Hughes, Brown, Abbas, Wolaver & Gervais, 2000; Cooper et al., 2003). If T-NRT varies

with different artefact cancellation techniques the same relation cannot be used. So there is a

need to study the variation, if any, in T-NRT for NRT recorded with different artefact

cancellation techniques.

The objectives of the present study were:-

1. To record NRT using three different artefact cancellation techniques, viz.,

forward masking, artefact template and alternating polarity, on a basal, medial and

apical electrode sites in the cochlea.

2. To compare the NRT recorded with the three different artefact cancellation

techniques.

3. To compare the T-NRT estimated using the visual detection, peak picker and

regression analysis techniques.

4. To compare the amplitude of the visually estimated T-NRT for NRT recorded

with the three different artefact cancellation techniques.

Method

Following method was used to study and compare the artefact cancellation and threshold

estimation techniques used in NRT. The method is explained under the following headings.

Participants

A total number of eight children (4 males and 4 females) with pre-lingual hearing loss of

severe to profound degree participated in the study. The children had no contra-indication for

cochlear implant surgery. All the participants were implanted with the Nucleus Freedom Contour

Advanced cochlear implant systems from Cochlear Corporation, Australia. The mean age of the

participants was 6.2 years (age range was from 2.6 to 13.3 years). Out of the eight participants, 7

were implanted in the right ear and one received the implant in the left ear. All the participants

had a post switch-on experience of electrical hearing with the cochlear implant system for at

least 3 months.


162

Instrumentation

Custom Sound EP (version 1.3) from Cochlear Corporation was the software that was

used to record the NRT from the participants implanted with Nucleus Freedom cochlear implant

systems. A laptop computer was used to run the Custom Sound EP (version 1.3) program. The

programming POD, an hardware interface, established the link between the speech processor of

the Nucleus Freedom cochlear implant system and the Custom Sound EP software installed in a

computer. The POD was connected to the speech processor of the Freedom Cochlear implant and

the other end of the programming POD was connected by a USB cable to the USB 2.0 port of the

laptop.

Procedure

All the measurements were done post-operatively with 4, 12 and 20 as the probe active

electrode which represented the positions in the basal, medial and apical part of the cochlea.

During the recording process the participants were comfortably seated and were allowed to

watch an animation film which held their attention. After the connection between the computer

and the speech processor was established the advanced NRT option was selected in the Custom

Sound EP (version 1.3). First an electrode impedance check was carried out in all participants to

rule out any open circuit or abnormally high electrode impedances in the selected electrode pairs.

NRT was then recorded, for each of the three electrodes, using three different artefact

cancellation techniques. The artefact cancellation techniques were forward masking, alternating

polarity and artefact template.

A test for optimized recording parameters (ORP) was carried out with each of the artefact

cancellation techniques to establish the optimum gain and delay measures for recording NRT. An

internal amplifier gain of 50 dB and a recording delay of 122µs were found to be optimal at all

the three electrodes, for all the participants and with each of the artefact cancellation techniques.

During NRT recordings the sequence of the use of the three different artefact cancellation

techniques was varied to rule out any sort of order effect.

In three of the eight participants NRT could be recorded only with forward masking and

alternating polarity methods of artefact cancellation as the children were awake during the

testing and did not co-operate for longer testing sessions. In the rest of the five participants NRT

was recorded with all the three different artefact cancellation techniques. This resulted in a total

data pool of 63 T-NRT values from 24 different electrode sites.

The NRT waveforms were recorded using the protocol described in Table 1 for the three

artefact cancellation techniques. Once the NRT recordings were made T-NRT values, given by

the peak picker and regression analysis of the software, were recorded. In the present study the

AutoNRT peak picker option was used. Peak-to-peak amplitude of visually determined N1 and

P2 was recorded for the visually estimated T-NRTs. The visually estimated T-NRT taken was

that which was agreed upon by a panel of three experienced audiologists so as to avoid any


163

individual bias. This was the T-NRT estimated based on the visual observation for the purpose of

the study. T-NRT was recorded:

for each of the three recording electrodes i.e., electrode number 4, 12, and 20.

with each of the threshold estimation techniques, for NRT recorded with the different

artefact cancellation techniques.

for each of the participant.

Table 1: Stimulating and recording parameters for NRT

Stimulation and recording

parameters

Artefact cancellation techniques

Forward Masking Alternating Polarity Artefact Template

Probe indifferent electrode MP 1 MP 1 MP 1

Probe pulse width 25 µs/phase 25 µs/phase 25 µs/phase

Probe rate 80 Hz 80 Hz 80 Hz

Probe inter phase gap 7 µs 7 µs 7 µs

Masker active electrode Probe active

electrode

NA NA

Masker indifferent electrode MP 1 NA NA

Masker current level Probe current level

+ 10

NA NA

Number of maskers 1 NA NA

Masker rate 100 Hz NA NA

Masker inter phase gap 7 µs NA NA

Masker probe interval 400 µs NA NA

Recording active electrode Probe active

electrode + 2

Probe active

electrode + 2

Probe active

electrode + 2

Recording indifferent

electrode

MP 2 MP 2 MP 2

Recording Gain and Delay Based on ORP Based on ORP Based on ORP

Number of sweeps 50 50 50

Measurement window 1600 µs 1600 µs 1600 µs

Effective sample rate 20 kHz 20 kHz 20 kHz

Artefact template current

level

NA NA Probe current level

– 15

Scaling factor NA NA Auto

No. of sweeps for template NA NA 500

Note: NA = Not applicable. MP1, MP2: Monopolar stimulation modes

The artefact cancellation techniques were statistically compared under the following stages:

Stage I: Comparison across different artefact cancellation techniques based on visually

estimated T-NRT at each of the three electrodes.

Stage II: Comparison across different artefact cancellation techniques based on peak picker

estimated T-NRT at each of the three electrodes.


164

Stage III: Comparison across different artefact cancellation techniques based on regression

analysis estimated T-NRT at each of the three electrodes.

Stage IV: Comparison across different artefact cancellation techniques based on the amplitude

of the visually estimated T-NRT at each of the three electrodes.

The methods of threshold estimation were statistically compared under the following stages:

Stage V: Comparison across different methods of threshold estimation for NRT recorded with

forward masking at each electrode.

Stage VI: Comparison across different methods of threshold estimation for NRT recorded with

artefact template at each electrode.

Stage VII: Comparison across different methods of threshold estimation for NRT recorded with

alternating polarity at each electrode.

Results & Discusson

For statistical comparison Friedman‟s test of significance was carried out across the

artefact cancellation techniques and threshold estimation methods in the all the seven stages

described earlier. Upon the presence of any significant statistical difference, Wilcoxon signed

rank test was carried out to find out which of the artefact cancellation techniques or threshold

estimation methods had significant difference. The results for seven different stages of

comparison are discussed below.

Stage I

The comparison across the artefact cancellation techniques based on the visually

estimated T-NRT in each of the electrodes revealed that there was no significant difference, even

at 0.05 level of significance in any of the electrodes. Table 2 shows mean and standard deviation

values for visually estimated T-NRT values with forward masking, alternating polarity and

artefact template on the 4th

, 12th

and 20th

electrodes.

Table 2: Mean and standard deviation (SD) values of visually estimated T-NRT for different

electrodes, using different artefact cancellation techniques

Recording

Electrode

Artefact Cancellation

Techniques

Mean Standard

Deviation

Electrode 4

Forward Masking 178.88 4.73

Alternating Polarity 181.63 4.21

Artefact Template 180.60 7.70

Electrode 12




Electrode 20





165

Although there was no significant difference seen comparison of the mean threshold

revealed that the mean threshold of the visually detected T-NRT was lowest for NRT recorded

with forward masking paradigm (Table 2 and Figure 1). In the forward masking paradigm the

stimulus artefact is recorded separately in the absence of any stimulus response as the nerve

fibers are put to refractory period. The stimulus artefact present in the probe alone condition and

probe-plus-masker condition is expected to be similar as in both cases the probe level is same.

Since the stimulus artefact is measured with precision it can be expected to be cancelled out and

the true neural response be recorded.

In the alternating polarity method of artefact cancellation it is not always true that the

neural response is identical in response to either anodic-leading or cathodic-leading biphasic

current pulses (Van Den Honert & Stypulkowski, 1987; Miller, Abbas, Rubinstein, Robinson,

Matsuoka & Woodworgh, 1998; Miller, Robinson, Rubinstein & Matsuoka, 1999). Klop,

Hartlooper, Briare and Frijns in 2004 reported that the N1 and P2 latencies are shorter for

cathodic-first (0.13 and 0.32 ms, respectively) than for anodic-first stimuli (0.16 and 0.38 ms,

respectively). As the N1-P2 peaks vary for anodic-leading and cathodic-leading biphasic current

pulses it may affect the averaged response and thereby the threshold.

In the artefact template technique the scaled down template of the artefact is always

measured at a lower probe level than the probe level used for measuring the NRT. The artefact

template is then scaled up accordingly when a recording is done at threshold level. The principal

limitation to this method, as reported by Brown (2004), is that the amplifier and tissue

conductance should be perfectly linear to produce exactly the same shaped artefact at a lower

current level which is generally not the case. As a result the scaled up template of the artefact can

be either overestimating or underestimating the actual artefact at certain probe level. In either

case it will distort the ECAP to a certain extent and hence might be expected to overestimate the

NRT threshold. It also requires a system with very low levels of ambient noise.

Stage II

The comparison across the different artefact cancellation techniques based on the peak

picker estimated T-NRT in each of the electrodes revealed that there was a significant difference

between forward masking and alternating polarity techniques for the 4th

electrode (p<0.05) and

20th

electrode (p<0.05). Table 3 shows mean and standard deviation (SD) values of T-NRT

estimated by peak picker, using the three different artefact cancellation techniques, for the 4th

,

12th

, and 20th

electrode. The mean T-NRT was lowest with the forward masking technique in all

the three electrodes.

It is to be remembered that there are two peak picker options. One is the AutoNRT peak

picker and the other one is the standard peak picker. In the present study the AutoNRT peak

picker was used because it was expected that the standard peak picker which can be user defined

will have good correlation with the visually estimated T-NRT.


166

Table 3: Mean and standard deviation (SD) values of peak picker estimated T-NRT for different

electrodes using different artefact cancellation techniques

Recording Electrode Artefact Cancellation Techniques Mean Standard Deviation

Electrode 4




Electrode 12




Electrode 20




The significant difference seen between forward masking and alternating polarity based

on peak picker estimated T-NRT is because of the fact that with the alternating polarity the peak

picker was identifying NRT tracings as response at a higher stimulation level that were very near

to actual T-NRT. Whereas with forward masking peak picker was identifying many NRT

tracings as response at very lower stimulation levels which were not NRT response as there were

no visible ECAP. The peak picker estimated T-NRT responses with artefact template were

generally near to that picked with the alternating polarity or in between that of the T-NRT

recorded with forward masking and alternating polarity. The mean T-NRT based on peak picker

was always lowest for NRT recorded with the forward masking paradigm, in all the electrodes,

as it detected many tracings as NRT responses at sub-threshold levels where no visible ECAP

were present.

Stage III

In this stage comparison across the artefact cancellation techniques based on the

regression analysis estimated T-NRT was made in each of the electrodes. Table 4 shows mean

and standard deviation (SD) value for T-NRT estimated by regression analysis using three

different artefact cancellation techniques on three different electrodes.

Table 4: Mean and standard deviation (SD) values T-NRT estimated from regression analysis for

different electrodes using different artefact cancellation techniques

Recording Electrode Artefact Cancellation Techniques Mean SD

Electrode 4




Electrode 12




Electrode 20





167

The comparison across the artefact cancellation techniques based on the T-NRT

estimated by regression analysis in each of the electrodes revealed that there was a significant

difference (p<0.05) between forward masking and alternating polarity, based on the T-NRT

established by regression analysis on the 4th

electrode. Though the mean differences were not

significant at the other electrodes with other artefact cancellation techniques, the T-NRT

estimated with regression analysis were again the lowest with the forward masking technique for

all the electrodes.

The extrapolated T-NRT given by linear regression analysis is based on the correct

responses identified by the NRT software at different stimulation levels and involves applying a

regression analysis to points on an input-output (or amplitude growth) function. Threshold is

determined as the level at which the regression line crosses zero amplitude (i.e., intercept of the

x-axis where y = 0). The T-NRT based on regression analysis can be affected if the peak picker

marks the amplitude measures in NRT tracings where there are actually no responses. Similar

finding was reported by Hughes (2006) wherein when the amplitude measures were unmarked

on the no-response waveforms, the linear regression based T-NRT became virtually the same as

the visual detection threshold. Since peak piker identification of correct NRT responses with

alternating polarity and forward masking different a significant difference, at times, can be

expected in the regression analysis based estimations for T-NRT recorded with these two

methods.

The regression analysis estimated T-NRT is also based on the amplitude growth function

linearity assumption. Typically the amplitude growth function is linear at higher current levels

and tails off near threshold but also flattens out at very high current levels, giving an over all

sigmoidal function (Botros, Dijk & Killian, 2006). These authors also reported that non-linearity

near threshold poses a difficulty for automated systems that are based on extrapolated threshold

method.

Stage IV

Comparison of the amplitude of the visually estimated T-NRT waveform recorded using

the three different artefact cancellation techniques revealed that there was a significant difference

between the amplitude of the T-NRT recorded with the three different artefact cancellation

techniques(p<0.05). Further analysis revealed significant differences between visually

established T-NRT amplitude recorded with alternating polarity and forward masking and

between visually estimated T-NRT amplitude recorded with artefact template and alternating

polarity for each the 4th

, 12th

and 20th

electrode(p<0.05). The amplitude of the N1 and P2 peaks

in the T-NRT tracings were recorded and the peak to peak amplitude between the N1-P2

complex was taken as the amplitude of the T-NRT. Table 5 shows mean and standard deviation

(SD) values of the amplitude (µV) of the visually estimated T-NRT recorded with the three

different artefact cancellation techniques on electrode number 4, 12 and 20. The lower mean

amplitude of visually estimated T-NRT recorded with alternating polarity as compared the mean

amplitude of the visually estimated T-NRT recorded with other two artefact cancellation


168

techniques can be observed in Figure 4. From Figure 4, it is noted that the NRT amplitude did

not vary much across the electrodes with alternating polarity technique. The amplitude of NRT

was always least with alternating polarity compared to artefact template and forward masking, in

all the electrodes. This is evident from the mean amplitude of the T-NRT recorded with

alternating polarity, which was always least for alternating polarity in all the electrodes. The

amplitude was highest for forward masking in the 4th

and 20th

electrode and, for artefact template

in 12th

electrode.

Table 5: Mean amplitude of the visually estimated T-NRT for different artefact cancellation

techniques on different electrodes

The lower amplitude for NRT recorded with alternating polarity can be attributed to the

fact that it is not always true that the neural response is identical in response to either anodic-

leading or cathodic-leading biphasic current pulses as reported by Van Den Honert and

Stypulkowski, (1987); Miller, Abbas, Rubinstein, Robinson, Matsuoka and Woodworgh, (1998);

Miller, Robinson, Rubinstein and Matsuoka, (1999). Klop, Hartlooper, Briare, and Frijns, (2004)

reported that the N1 and P2 latencies are shorter for cathodic-leading (0.13 and 0.32 ms

respectively) than for anodic-leading stimuli (0.16 and 0.38 ms respectively). Since the N1 and

P2 is recorded at different latencies with anodic-leading and cathodic-leading biphasic current

pulses they will lie at different sampling points during recording for half of the anodic-leading

biphasic current pulse stimuli and half of the cathodic-leading biphasic current pulse stimuli.

This will lead to lesser N1-P2 peak-to-peak amplitude recorded after averaging, when compared

to the averaged N1-P2 peak-to-peak amplitude of any other method where the N1 and P2

latencies fall at similar latencies and hence at similar sampling points for each stimulation. The

findings of this study is consistent with that of Hughes, Abbas, Brown, Behrens and Dunn

(2003), who reported that the amplitude of the NRT recorded with alternating polarity method

tends to be significantly smaller than that obtained with the subtraction method (r = 0.97, p <

0.0001) yielding higher thresholds with alternating polarity (r = 0.86, p = 0.01).

Recording Electrode Artefact Cancellation Techniques Mean SD

Electrode 4




Electrode 12




Electrode 20





169

Electrode Number

20124

Me

an

Vis

ua

l T-N

RT

cu

rre

nt

leve

ls

225

200

175

150

125

100

ACT

AP

AT

FM

Electrode Number

20124

Me

an

Pe

ak

Pic

ker

T-N

RT

cu

rre

nt

leve

ls

225

200

175

150

125

100

ACT

AP

AT

FM

Fig. 1: Bar diagram of the mean T-NRT Fig. 2: Bar diagram of the mean T-NRT

estimated visually with the different artefact estimated with peak picker for different

cancellation techniques artefact cancellation techniques

Electrode Number

20124

Me

an

Re

gre

ssio

n T

-NR

T c

urr

en

t le

vels

225

200

175

150

125

100

ACT

AP

AT

FM

Electrode Number

20124

Me

an

Am

plit

ud

e (

µV

) o

f vi

sua

l T-N

RT

20

18

16

14

12

10

8

6

ACT

AP

AT

FM

Fig. 3: Bar diagram of mean T-NRT estimated Fig. 4: Bar diagram of the mean

by regression analysis for different artefact of visually estimated T-NRT with

Cancellation techniques. different artefact cancellation techniques

Note: ACT = artefact cancellation techniques; AP = alternating polarity; AT = artefact template;

FM= forward masking

Stage V

The visual, peak picker and regression analysis estimated T-NRT for NRT recorded with

forward masking were compared at each of the 4th

, 12th

, and 20th

electrode. Statistical

comparison revealed that when forward masking was used as an artefact cancellation technique,

there were significant differences between the different methods of estimating T-NRT (p<0.05).

Further analysis revealed that when forward masking was used significant difference was seen

between T-NRTs that were visually estimated and T-NRTs that were estimated using the

regression analysis and the peak picker methods (p<0.05). No statistical difference was observed

even at 0.05 level of significance between the peak picker estimated and regression analysis

estimated T-NRTs. Similar findings were observed in all the electrodes.


170

There was no significant difference between peak picker estimated and regression

analysis estimated T-NRT, when forward masking was used, because of the fact that the

regression based extrapolated threshold considers the responses picked up by the peak picker and

involves applying a regression analysis to points on an input-output (or amplitude growth)

function. The same trend was observed in every case and no significant difference between peak

picker and regression analysis estimated T-NRT was seen in any electrode with any artefact

cancellation technique.

A significant difference between visual and peak picker based T-NRT for NRT/ECAP

recorded with forward masking as artefact cancellation technique was seen because of the fact

that the peak picker identified NRT tracings as responses even where no visible ECAP existed.

The present finding which show that peak picker identified NRT tracings with no visible ECAP

as responses is consistent with the findings of Hughes (2006).

Figure 5 depicts that when NRT waveforms recorded with forward masking as the

artefact cancellation technique the peak picker identified an NRT response at current levels

where no visible ECAP can be observed. The actual visually detected threshold was at 183

current levels. Also in Figure 5 we can see the improper marking of the P2 latency even when

the NRT tracing is correctly identified as a response. For example, the P2 latency was picked too

late by the peak picker for NRT tracing with 186 current levels. Also, P2 is expected to reduce in

latency with increase in stimulus level. However, the P2 latency picked for NRT tracing with

183 current levels is less than the P2 latency picked for NRT tracing with 190 current levels.

As discussed earlier the regression analysis based estimation of T-NRT involves applying

a regression analysis to points on an input-output (or amplitude growth) to the responses picked

by the peak, so an incorrect marking of responses by the peak picker will also affect the

regression based T-NRT. This is why a significant difference was seen between visual and

regression based T-NRT with forward masking as artefact cancellation technique for recording

NRT. Similar results of incorrect NRT response identification by peak picker affecting the

regression T-NRT was reported by Hughes (2006).

Stage VI

Similar to NRT recorded with forward masking NRT recorded with artefact template also

had significant differences between the estimated T-NRT based on visual detection and peak

picker and between the estimated T-NRT based on visual detection and regression analysis. The

findings can be discussed on similar lines as above. The peak picker picked up incorrect NRT

tracings as responses for NRT recorded with artefact template as artefact cancellation technique,

even when there was no visible ECAP. This is understood in Figure 6 where NRT tracings at 161

and 164 current levels have been picked as NRT responses. The incorrect placing of cursors of

N1 and P2 peaks can also be observed.


171

Stage VII

Comparison of the visual, peak picker and regression estimated T-NRT for NRT recorded

with alternating polarity as artefact cancellation technique did not show any significant

difference in any of the electrodes. The reason can be attributed to the ability of the peak picker

to identify NRT responses correctly when NRT was recorded with alternating polarity as artefact

cancellation technique. This is understood from Figure 7. It is to be noted that visually NRT with

175 current levels was taken as the T-NRT and the peak picker picked up 174 current levels as

the T-NRT.

.

Fig. 5: Peak picker marked NRT waveforms Fig. 6: Peak picker marked NRT waveforms

recorded with forward masking at different recorded with artefact template at different

current levels current levels

Fig. 7: Peak picker marked NRT waveforms recorded with alternating polarity at different current levels

Conclusion

The present study shows that all the three artefact cancellation techniques might be used

with confidence for recording NRTs for clinical purpose. A visual estimation T-NRT if used will

not result in significant differences in T-NRT. However, amplitude of NRT recorded with

alternating polarity will be consistent as compared to the other two artefact cancellation

techniques. The use of the peak picker and regression analysis techniques for determining T-

NRT should be done with caution. Discarding incorrectly identified peak picker responses will

improve the efficacy of the regression analysis T-NRT.


172

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(1999). Summary of results using the Nucleus CI24M implant to record the electrically

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measures ECAP thresholds with the Nucleus FreedomTM cochlear implant via machine

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relationship between EAP and EABR thresholds and levels used to program the Nucleus

24 speech processor: Data from adults. Ear and Hearing, 21, 151-163.

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Plant, K., Dees, C.D. & Murray, B. (2003). Comparison between NRT-based MAPs and

behaviorally measured MAPs at different stimulation rates – a preliminary study.

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“Comparison of two methods used to measure the ECAP in subjects implanted with the

Clarion CII device.” Paper presented at the Third International Symposium and

Workshops on Objective Measures in Cochlear Implants, Ann Arbor, MI, 2003.

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of EAP thresholds with MAP levels in the Nucleus 24 cochlear implant: data from

children. Ear and Hearing, 21, 164-174.

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the stimulus artefact in electrically evoked compound action potential measurements.

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174

Speech-Evoked Auditory Late Latency Response (ALLR) in hearing

aid selection

Shruti Kaul & C S Vanaja

Abstract

Cortical auditory evoked potentials (CAEPs) offer the possibility of evaluating the

effectiveness of hearing instruments in infants and older children who have limited behavioural

repertoire due to developmental delay or other disabilities. The present study was an attempt to

investigate the usefulness of auditory late latency responses (ALLR) evoked using speech stimuli

in hearing aid selection. The study consisted of two groups of participants. Group I included

children with normal hearing and Group II included children with hearing impairment both in

the age range of 5-7 years. CAEPs/ALLR were recorded for Group I participants for three

naturally produced speech sounds, /i/, /m/, /∫/, presented through a loud speaker at 65 dB SPL.

The CAEPs/ALLR was recorded for the same stimuli without a hearing aid and with two pre

selected hearing aids for Group II. For Group II participants functional gain measurements

were also carried out with the two pre selected hearing aids. The CAEPs (P1-N1-P2-N2) were

analyzed for peak latencies and amplitude of N1-P2 complex. Analyses of the data revealed that

all the three stimuli elicited waveforms that were distinct from each other. Significant effect of

stimuli was demonstrated for children with normal hearing and children with hearing

impairment wearing a hearing aid. Significant effect of age was not observed though a trend of

decrease in latency was noted for children with normal hearing. Comparison between aided and

unaided conditions revealed that in unaided conditions the responses were absent but the

responses were present in the aided condition. There was no statistically significant difference

between the latencies and amplitude of CAEP/ALLR peaks for the two populations when the

children with hearing impairment were wearing the most appropriate hearing aid. These

findings highlight that P1-N1-P2-N2 responses are efficient in reflecting the benefit of hearing

aid at least at a gross level.

Introduction

The increased emphasis on early identification and remediation of hearing loss has

resulted in considerable interest in using the cortical auditory evoked potentials (CAEPs) to

assess clinical populations in whom behavioural measures, speech detection and discrimination

are difficult to obtain (e.g., infants, children and difficult to test population). The obligatory

CAEPs, also called as auditory late latency responses (ALLR) can be recorded in response to a




175

variety of auditory stimuli ranging from simple tonal stimuli to complex speech stimuli such as

consonant-vowels syllables, words and even full sentences (Naatanen & Picton, 1987). These

responses can be reliably recorded from individuals of all age groups including well babies as

well as babies with low birth weight (Krutzberg et al. 1984).

Attempts have been made to record these potentials in individuals using hearing aid. In

one of the earliest study evaluating the benefit of CAEPs/ALLR, Rapin and Grazianni (1967)

found that a majority of their 5 to 24 months old infants with severe to profound sensori-neural

hearing loss had cortical ERPs threshold 20 dB lower/better in comparison to the unaided

thresholds for click and tonal stimuli. Most of the research later on concentrated on evaluation

hearing aid benefit using speech stimuli. In one of the recent studies Tremblay, Billings, Friesen

and Souza (2006) obtained CAEPs using amplified speech sounds /si and /∫i/ from 7 normal

hearing young adults. Participants were retested within a period of 8-days in both aided and

unaided conditions. Results revealed that speech evoked CAEPs can be recorded reliably in both

aided and unaided conditions. It was observed that hearing aids that provide a mild high

frequency gain only subtly enhance peak amplitudes relative to unaided conditions. If the

consonant-vowel (CV) boundary is preserved by the hearing aid, it can also be detected neurally

resulting in different neural response patterns for /si/ & /∫i/. It was concluded that speech evoked

cortical potentials can be recorded reliably in individuals wearing hearing aids.

In a similar study Tremblay, Kalstein, Billings and Souza (2006) recorded CAEPs in

adult hearing aid users using acoustic change complex (ACC). Seven adults (50-76 years) with

mild to severe sensori-neural hearing loss participated in the study. When presented with two

identifiable CV syllables (/si and ∫i/) the neural detection of CV transitions as indicated by the

presence of a P1-N1-P2 response was different for each speech sound. More specifically, the

latency of the evoked neural response coincided in time with the onset of the vowels. Hinduja,

Kusari and Vanaja (2005) investigated changes in ALLR as a function of hearing aid gain in 6

hearing impaired children having moderately severe to profound hearing loss. The aided

behavioral thresholds and aided ALLR responses were obtained with two hearing aids in all the

participants. One low gain hearing aid yielding behavioral threshold outside speech spectrum

called Poor Hearing aid and one hearing aid yielding thresholds within the speech spectrum

called Good Hearing aid was considered for the study. Results showed that the amplitude was

larger and the latency was shorter for ALLR recorded when the good Hearing aid was worn

when compared to that obtained while wearing the poor hearing aid.

Thus limited research carried out indicates that CAEPs/ALLRs can be reliably recorded

from individuals wearing hearing aids. However, there is a dearth of literature on usefulness of

CAEPs/ LLR in evaluating hearing aid benefit using natural speech tokens. Also it is not known

whether CAEPs can be useful in comparing performance among different hearing aids. If it can

then this measure will be a useful tool in selection, fitting and validation of hearing aids in

difficult to test population. It might also be instrumental in monitoring the performance during


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and after the auditory training. Therefore the present study was designed to investigate the

following aims:

To compare the CAEP waveform obtained for naturally produced speech tokens, /i/, /m/

and /∫/ in children with normal hearing.

To evaluate the usefulness of CAEPs for naturally produced speech tokens, /i/, /m/ and /∫/

in validation of appropriate hearing aid.

Method

The following method was used to investigate the usefulness of ALLR in evaluation of

hearing aid benefit and also to develop norms for ALLR for natural speech tokens. All the

measurements were carried out in an acoustically treated double room situation where the

ambient noise levels were within the permissible levels (ANSI, 1991).

Participants

Two groups of participants were included in the study. Group I included 15 children with

normal hearing in the age range of 5-7 years and Group II included 10 children with hearing

impairment in the age range of 5-7 years. Participants of Group I had hearing sensitivity of less

than 15 dBHL at octave frequencies between 250 Hz and 8000 Hz. The middle ear functioning

was normal and there was no history of any otologic, neurologic problems. Participants of Group

II had pure tone thresholds in the range of 70 to 100 dBHL. They also had normal middle ear

functioning and there was no history of any otologic and neurologic problems.

Instrumentation

A calibrated 2-channel diagnostic audiometer with sound field facility was used to carry

out the pure tone audiometry and functional gain measurements. A calibrated immitance meter

was used to examine the middle ear functioning. Intelligent Hearing System (version 2.39) with

matched loud speakers was used to record and analyze the late latency responses.

Materials used for testing

Stimuli for recording LLR were natural speech segments -/i/, /m/, /∫/. These were spoken

by a normal adult female Kannada speaker into a unidirectional microphone connected to the

computer. The recording was done using Praat software with a sampling rate of 16000 Hz. The

duration of the stimuli was kept constant at 250 ms across all the speech sounds. The wave file

was then converted to stimulus file for ALLR recording using „Stim conv‟ provided by the

Intelligent Hearing System (version 2.39).

Test procedure for Group I

Pure tone thresholds were obtained in the sound field for octave frequencies between 250

Hz and 8000 Hz for air conduction. Tympanometry and acoustic reflexes were carried out to rule

out any middle ear pathology. ALLR recording was done for the participants who met the

selection criteria.


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ALLR recording: Participants were comfortably seated in order to ensure a relaxed posture and

minimum rejection rate. Loud speaker delivering the stimuli was placed at a distance of one

meter and at a 0º azimuth to the test ear. Speech evoked LLR recording was done when the child

was awake. „Mehandi‟ was drawn on children‟s hands to ensure that the child is awake and quiet.

Conventional electrode montage was used with the non inverting electrode on Fz, inverting

electrode on the mastoid of the test ear and common electrode on the mastoid of the non test ear.

It was ensured that the electrode impedance values were less than 5kΩ and the inter electrode

difference was less than 3kΩ. ALLR were recorded using the test protocol given in Table 1.

Table 1: Protocol used for ALLR recording

Stimuli /i/, /m/, /∫/

Stimulus level 65 dBSPL

Transducer Loudspeakers at 0º azimuth

Rate 1.1/sec

Polarity Alternating

Filters 1-30 Hz

Notch filters On

Number of channels Single channel

Recording time window 500ms

Amplification 50X

Sweeps 200

Number of repeats 2

Test procedure for Group II

Similar to the procedure used in the Group I pure tone thresholds, tympanometry and

acoustic reflexes were obtained for the participants of Group II. Two digital hearing aids were

pre-selected and programmed based on the audiological findings. Functional gain measurements

as well as unaided and aided ALLR were carried out with pre-selected hearing aids. These two

test procedures were used to rate the hearing aids regarding their suitability to the children with

hearing impairment.

Functional gain measurements: Unaided and aided pure tone thresholds were obtained for FM

tones at octave frequencies between 250 Hz and 8000 Hz. The stimuli were presented through

the speakers placed at distance of one meter and at 45º azimuth. Conditioned responses were

obtained across the frequencies

ALLR recording: ALLRs were recorded separately for the three stimuli, /i/, /m/, /∫/ without the

hearing aid as well as with pre selected hearing aids. The procedure used for recording ALLR

was same as that used for Group I.

Analysis

The waveforms were analyzed and P1-N1-P2-N2 peaks were identified by two

audiologists who were unaware of the test conditions. The audiologists ranked the unaided and


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aided ALLR obtained for Group II as I, II, III. Latency and amplitude of the identified peaks

were noted and suitable statistical analysis was carried out to investigate the aims of the study.


Robust P1-N1-P2-N2 responses were obtained in all the participants of Group I for all the

three naturally produced speech tokens /i/, /m/, /∫/ and the responses were robust in Group II

when the children were wearing the most appropriate hearing aid. The responses were replicable

in all the participants. The data obtained were analyzed to investigate the aims of the study using

the SPSS software.

P1-N1-P2-N2 responses in children with normal hearing: P1-N1-P2-N2 responses could be

recorded from all the 15 participants for all the three natural speech tokens /i/, /m/, /∫/ presented.

The data obtained were tabulated and statistical analysis mixed design ANOVA was carried out

to assess the effect of age and stimuli on latency and amplitude of P1-N1-P2-N2 responses.

Effect of stimuli

Figure 1: Responses for /i/, /m/ and /∫/ stimuli in children with normal hearing

The mean and the standard deviation of the latencies obtained for the three stimuli across

the three age groups are tabulated in Table 2. It can be observed from the table that the latencies

for stimuli /i/ were shortest while /∫/ had the longest latencies. Figure 1 shows the representative

sample of waveform for the three different stimuli.

Repeated measure ANOVA revealed that there was a main effect of stimuli on the

latency of all the waves. Bonferroni‟s multiple comparison test was done to see the pairwise

differences between the stimuli. The test results indicate that P1 and N2 responses to all the three

stimuli are significantly different (at 0.01 level of significance) from one another. But the latency

of N1 and P2 peaks showed a significant difference between /i/ and /m/ as well as between /i/

and /∫/ stimuli at 0.05 level of significance but there was no significant difference between the

latencies for /m/ and /∫/.

/i/

/m/

/∫/


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Table 2: P1-N1-P2-N2 latencies in ms for the three stimuli across the age groups in children with

normal hearing

Peaks

Age

Stimuli

/i/ /m/ /∫/


P1

5-6 years 101.34 16.84 113.40 20.74 131.42 17.94

6-7 years 97.35 10.24 102.60 6.53 130.42 9.16

7-8 years 86.22 3.56 93.96 5.27 118.92 19.71

N1

5-6 years 172.94 18.55 199.88 28.21 227.52 30.50

6-7 years 169.80 14.33 196.55 18.00 216.57 28.53

7-8 years 152.08 17.14 176.70 25.64 215.02 47.40

P2

5-6 years 226.74 22.79 266.74 24.96 291.76 30.25

6-7 years 211.63 12.74 255.50 17.52 289.20 28.06

7-8 years 201.38 31.16 238.86 29.04 283.14 42.57

N2

5-6 years 302.20 32.20 330.24 23.92 394.14 43.02

6-7 years 278.30 19.39 339.90 13.16 390.03 16.83

7-8 years 273.56 34.25 312.74 34.99 339.38 45.15

The N1-P2 responses were the most prominent peaks. Hence only amplitude of N1-P2

was measured. Table 3 shows the mean amplitude and standard deviation of N1-P2 complex for

the three stimuli. It can be observed from the table that the responses for the high frequency

stimuli, /∫/, had smaller amplitude when compared to responses for stimuli /i/ and /m/ which had

dominant spectral energy at low frequencies. A main effect of stimuli on N1-P2 amplitude was

yielded when repeated measures of ANOVA was carried out (F (2, 35) = 8.82, P< 0.05).

Bonferroni‟s multiple comparison test revealed that there was a significant difference between /∫/

and /m/ at 0.05 level of significance but no significant difference was seen between /i/ and /m/

and between /i/ and /∫/.

The results of the present study are in accordance to the findings of Agnug et al. (2006)

wherein /i/ had shortest latency followed by /כ/, /m/, /a/, /u/, /s/ and /∫/ had longest latency. In the

same study latency differences across the different vowels were studied wherein high front

vowel /i/ had earlier latencies than latency for low mid- back vowel /u/.

Table 3: N1-P2 amplitude in µv for the three stimuli and across age groups in children with

normal hearing

Amplitude

Age

Stimuli

/i/ /m/ /∫/


N1-P2

5-6 years 3.05 0.83 3.72 0.76 2.30 1.24

6-7 years 3.35 0.69 3.45 1.98 1.62 1.01

7-8 years 2.25 0.89 2.31 1.23 1.99 0.81


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The responses for the mid vowel /a/ occurred between these two latencies. Obleser, Eultiz

and Lahiri (2004) found that the back vowel /o/ resulted in later latency when compared to the

latency of the front vowel /ø/ and they also observed that front vowels activate a more inferior

and anterior source compared to back vowels. Similar results were reported by Makela, Alku,

Makinen, Tiitinen (2005) and they concluded that cortical representation of vowels reflects the

phonological features of speech. However, phonological features alone do not account for

latency differences as suggested by Agnug et al. (2006) wherein they found that in Australian

English, /כ/ is further retracted than /u/ but still low-back vowel /כ/ did not have the longest

latency, but occurred at a similar latency to the mid vowel /a/. The investigators accounted for

this difference to the large F2-F1 differences in the vowels. This might also be the reason for

obtaining differences in latencies for /i/, /m/ and /∫/ stimuli in the present study. The F2-F1

difference is approximately 700 Hz to 800 Hz for /m/ speech sound and hence might be resulting

in response that occurs at a different time compared to the vowel /i/ which has a larger F2-F1

difference. Tremblay et al. (2003) also observed that when the stimuli had an early onset of

vocalic portion as in /∫i/ early P1-N1-P2-N2 latency was obtained when compared to the /si/

stimuli where the vocalic portion had comparatively later onset.

In the present study the natural speech tokens dominated by high frequency spectral

energy /∫/ elicited P1-N1-P2-N2 responses with smaller N1-P2 amplitudes than speech sounds

that had dominant spectral energy in the low frequencies. These findings are consistent with the

results of Agnug et al. (2006), wherein the low frequency dominant stimuli (/m/, /a/, /u/, /i/) had

higher amplitudes compared to the high frequency dominant stimuli (/s/, /∫/). Similar findings

have been reported for the tonal stimuli with low frequency tones eliciting cortical responses

with larger amplitudes than high frequency tones (Jacobson, Lombardi, Gibbens, Ahmad &

Newman, 1992). Shestakova, Brattico, Soloviev, Klucharev, Hotiliainen (2004) have reported

that amplitude and source locations of N1m differed between the vowel categories and vowels

with similar spectral envelopes had closer cortical representations than those where spectral

differences were greatest. Yeltin, Roland, Chriestensen and Purdy (2004) have reported that

cortical areas that respond to low frequency auditory information are located more superficially

(i.e. closer to the surface of scalp) than cortical regions for high frequencies. Hence low

frequency stimuli may activate more superficial cortical regions and produce larger amplitude

CAEPs than high frequency speech sounds when surface scalp electrodes are used. However, as

it is known the complexity of speech stimuli are not based solely on the frequency effect. Agnug

et al. (2006) found that /כ/ (dominated by lowest frequency spectral energy) produced N1-P2

amplitudes that were not significantly different from /s/ and /∫/ response amplitudes. The results

of the present study and the earlier reports indicate that the latency and amplitude of waves

depend on the stimulus used for evoking the responses and the latency and amplitude probably

depend on the spectral content of the stimuli used.

Effect of Age

A general trend can be observed from Table 1 wherein there is a decrease in latency from

5 to 8 years of age for all the four peaks P1, N1, P2, N2. However, mixed design ANOVA

revealed that age did not have a main effect on the latency and amplitude measures (P > 0.05

level of significance). No age related trend was observed for the N1-P2 amplitude and results of


181

mixed design ANOVA revealed that there was no main effect of age on the amplitude of N1-P2.

Also no significant interaction between age and stimuli was observed.

Though not statistically significant even in the present study there was a decrease in

latency of all the peaks with increase in age. Previous studies also report maturational changes

during the early childhood. Ceponiene, Rinne and Naatanen (2002) reported that children‟s ERPs

are dominated by P1 and N1 peaks and the N1 emerges between 3 to 4 years of age. In the study

a long preponderance of the N2 potential was noted. Mc Pherson and Starr, (1993) also reported

that P1-N1-P2-N2 decrease in latency from birth up to 5 years of age. The N2 demonstrates a

greater negativity in this age group than the older age groups. It was also reported that peak

amplitudes and latencies for P2 and N2 remain relatively constant for ages between 5 to 16 years

(Mc Pherson & Starr, 1993). This was attributed to increase in myelination and improvements in

synapse efficacy (Kraus et al. 1993).

The present study demonstrates a more pronounced decrease in latency and amplitude for

P1 than for N1, P2, and N2 responses. This is consistent with investigations by Sharma, Martin,

Roland, Sweeny, Gilley and Dorman (2005) who revealed that P1 latency is the biomarker for

the development of auditory pathways in children with hearing impairment who received

intervention through conventional hearing aids and cochlear implants. The reason for not finding

a statistical significant effect of of age might be because of small sample size included in age

group. The effect of age needs to be further investigated on a larger sample size.

P1-N1-P2-N2 responses in children with hearing impairment: P1-N1-P2-N2 responses were

recorded for natural speech tokens /i/, /m/ and /∫/, in both unaided and aided condition, at 65

dBSPL for 10 children with hearing impairment.

P1-N1-P2-N2 responses in unaided condition: P1-N1-P2-N2 responses were absent in the

unaided condition for all the participants. This is probably due to severity of hearing loss. The

participants had hearing loss that ranged from severe to profound (71-90 dBHL and >91 dBHL)

but the stimuli were presented at normal conversational level (65 dBSPL) as the aim of the study

was to assess the benefit of the hearing aid at conversational level.

Figure 2: Responses for /i/ stimuli in unaided (uppermost), rank II (middle) and rank I (lower

most) hearing aids


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Polen (1984) found that moderate to severe sensori-neural hearing loss resulted in

prolongation of N1-N2 and P300 latencies and a reduction in N2 amplitude in comparison with

results from normal hearing participants. But the effect of hearing loss needs to be further

investigated.

Effect of amplification:

Speech evoked P1-N1-P2-N2 responses were reliably recorded in all the children while

they were wearing a hearing aid. The effects of amplification were analyzed statistically by

comparing aided and unaided responses for latency and amplitude measures.

Figure: 3 Responses for /m/ stimuli in unaided (uppermost), rank II (middle) and rank I (lower

most) hearing aids

Based on the functional gain measurements the hearing aids were ranked as I and II. The

benefit from amplification was greater with the hearing aid ranked as I when compared to that

from the hearing aid ranked as II. The mean and the standard deviation across the stimuli for

two hearing aids are tabulated in Table 4.

Figure 4: Responses for /∫/ stimuli in unaided (uppermost), rankII (middle) and rankI (lower

most) hearing aids


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From the Table 4, it can be observed that, similar to that obtained in children with normal

hearing, the responses for /i/ had the shortest latency and responses to /∫/ had the longest latency

for both the hearing aids. Figure 2, 3 and 4 represent the unaided, aided response for the three

stimuli, /i/, /m/ and /∫/, respectively. Repeated measure ANOVA revealed that there was no main

effect of stimuli on P1, P2, and N2 response latencies but there was a main effect of stimuli on

latency of N1. Bonferroni‟s multiple comparison test showed that there was a significant

difference between /i/ and /m/ and between /i/ and /∫/ (P< 0.05) while no significant difference

was found between /m/ and /∫/ for for latency of N1 with the rank I hearing aid. On the contrary

for the rank II hearing aid no effect of stimuli was observed for P1-N1-P2-N2 responses.

The N1-P2 amplitude between the rank I and rank II hearing aids were also compared.

The mean and standard deviation for N1-P2 amplitude with the two hearing aids is tabulated in

Table 4. It can be observed from the table that /∫/ has the lowest amplitude compared to /i/ and

/m/ and /i/ has better amplitude than /m/ but there was no effect of stimuli on amplitude of N1-P2

complex for both the hearing aids as revealed by repeated measure ANOVA (P>0.05). These

findings are similar to findings in the normal hearing children. But for rank II hearing aid it was

seen that the amplitude of N1-P2 complex was reduced and the overall morphology was poorer

when compared to rank I hearing aid.

Table 5. P1-N1-P2-N2 latencies & amplitude for the stimuli for children with hearing

impairment wearing hearing aid

Latency/

Amplitude

Stimuli Rank I hearing aid Rank II hearing aid

Mean SD Mean SD

P1 latency

/i/ 92.70 20.42 119.92 42.15

/m/ 104.73 30.34 119.97 39.64

/∫/ 127.56 36.23 145.76 37.33

N1 latency

/i/ 159.17 28.87 214.87 48.67

/m/ 189.77 18.98 216.10 42.48

/∫/ 221.55 50.11 233.53 42.17

P2 latency

/i/ 237.82 25.87 276.61 23.92

/m/ 270.0 35.92 284.91 52.31

/∫/ 284.17 53.18 333.58 40.27

N2 latency

/i/ 308.13 48.11 365.10 33.35

/m/ 339.41 43.42 374.34 44.84

/∫/ 366.41 45.25 411.50 17.58

N1-P2

amplitude

/i/ 5.04 2.44 4.2 2.96

/m/ 4.76 2.25 3.5 1.25

/∫/ 2.97 1.32 2.5 1.98

Comparison between unaided and aided performance

In unaided condition, the P1-N1-P2-N2 responses were absent for all the participants

with hearing loss but in aided condition the responses were present for all the three stimuli for all


184

the participants for both the hearing aids. This suggests that the children benefited from the use

of hearing aid.

Comparison between rank I and II hearing aids

The two hearing aids were compared for latency and amplitude measures across the

stimuli using the Paired „t‟ test. The results revealed that there is a significant difference between

the N1-P2 amplitudes and a significant difference was found for N1 and P2 latencies for /i/

stimuli but no significant difference was found for the P1, N2 latencies. The results hence reveal

that N1, P2 latencies are critical in demonstrating the usefulness of amplification across the

speech stimuli. This has also been supported by various investigators who have used N1 latency

and N1-P2 amplitude for assessing usefulness of P1-N1-P2-N2 responses in fine discrimination

tasks (Agnug et al. 2006).

From the results thus obtained it can be observed that the amplitude measure is more

sensitive in differentiating between rank I and rank II hearing aid. In the present study the testing

was carried at a constant SPL for both the hearing aids. More the gain offered by the hearing aid

higher is the output delivered to the ear and the higher level reaching the cochlea probably

activated more number of fibers which in turn resulted in larger amplitude. It has been reported

that the amplitude of auditory evoked potentials depend on the number of fibers responding

(Hall, 1992). But the latency depends on the processing time and not on the number of fibers

responding and probably the difference in processing time across the participants did not result in

significant difference for the two hearing aids for the latency measure. It has been reported that

the effect of intensity on latencies of ALLR is not significant at moderate levels (Hall, 1992).

Comparison between children with normal hearing and children with hearing impairment

wearing most appropriate hearing aid

The latencies of P1, N1, P2, N2 and amplitude of N1-P2 peaks of the two groups of

participants were statistically compared using independent sample „t‟ test. The results reveal that

children with hearing impairment with most appropriate hearing aid (Rank I hearing aid) had

responses that were not statistically different from the normal hearing children. Hearing aids

compensated for the loss of audibility and there was no neural involvement, hence there was no

significant difference between the two groups of participants. Also, Group II participants were

hearing aid users since 2 years and were receiving auditory training. These results are supported

by those of Ponton et al. (1996) who reported that when deaf children were fitted with cochlear

implant P1 latency showed same rate of maturation in normal hearing children and children who

were fitted with the implant.

Efficacy of CAEPs/ALLR in ranking hearing aid benefit

Two judges who were unaware of the test conditions were requested to rate the hearing

aids based on ALLR responses. The agreement between the two judges was analyzed. It was

observed that there was 80% agreement between the two judges for responses to /i/ stimuli.

There was only 50% agreement between the two judges for the response to /⌡/ stimuli. The


185

response for stimuli /m/ showed 60% agreement between the judges. It was also observed that as

the waveform morphology became poorer agreement between the judges reduced. The probable

reason might be that one of the judges was more experienced in judging the speech evoked

ALLR than the other judge.

For investigating the efficacy of ALLR in hearing aid validation the ranking of hearing

aids based on ALLR was compared with the ranking done based on functional gain

measurement. A third audiologist judged the ALLR whenever there was a discrepancy between

the two judges and the ranking was carried out based on the decision of the majority of the

judges. Comparison of the ranking based on ALLR responses and functional gain measurements

showed that there was 80% agreement for the /i/ stimuli followed by /m/ which demonstrated

70% agreement and lowest agreement was found for /⌡/ stimuli. The reason for not finding high

agreement for all the stimuli might be because the functional gain was based on thresholds for

tonal stimuli. Behavioural aided and unaided responses for the three stimuli (/i/, /m/ and /∫/)

would have thrown more light on the perception the stimuli.

Conclusions

From the above results it can be observed that: ALLR responses can be recorded for the

speech stimuli in children with normal hearing and children with hearing impairment wearing a

hearing aid. The responses obtained for the three stimuli, /i/, /m/ and /∫/, resulted in distinct

responses indicating that the stimuli are coded differently in the auditory system. Among the

three stimuli /i/ resulted in better morphology, shorter latency and high amplitude than /m/ and /∫/

stimuli indicating that the vowels are better coded than the consonants. A trend of decreasing

latency with increase in age indicates that probably maturation is occurring at this stage. With

most appropriate hearing aids the responses were present for /i/, /m/ and /∫/ stimuli and they were

not significantly different from that of children with normal hearing demonstrating the usefulness

of the hearing aid. The hearing aid which was not suitable according to the functional gain

measurements also showed poor responses in the ALLR recording, hence indicating that the

ALLR responses are useful in differentiating between the more and less suitable hearing aid.

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187

Brainstem Responses to Speech in Normal Hearing and Cochlear

Hearing Loss Individuals

Sumesh K & Animesh Barman

Abstract

Studying the neural encoding of speech sounds provides insight into some of the auditory

processes involved in normal communication. Auditory brainstem evoked responses to speech

provide direct information about how the sound structure of a speech syllable is encoded in the

auditory system. Individuals with cochlear hearing loss have consistently shown difficulties in

perceiving place and manner cues of consonants. The current study aimed at determining the

effect of cochlear hearing loss, stimulus presentation level (equal SL and equal SPL) on

brainstem responses to speech. The ABR and FFR were recorded for the synthetic speech stimuli

/da/ in 22 normals and 22 cochlear hearing loss (PTA < 55 dBHL) individuals at 80 dBnHL and

40 dB SL. Results revealed that the cochlear hearing loss showed reduced amplitude and

prolonged wave latency even at equal sensational level. This effect was adverse with the increase

in severity of hearing loss. The temporal fine structure coding was adversely affected with

increase in the hearing loss which is reflected by the poor coding of F0 and its formant (F1).

Introduction

The neural encoding of sound stimulus begins at the auditory nerve and continues till the

cortex via the auditory brainstem. Brainstem responses to simple stimuli (e.g., clicks, tones) are

well defined and widely used in clinical practice in the evaluation of auditory pathway integrity

(Moller, 1999; Starr & Don, 1988). However, the role of brainstem in processing a complex

signal, varying in many acoustic dimensions continuously over time, such as a speech syllable

have recently become a subject of great interest with the help of conventional techniques of

recording evoked potentials.

Studying the neural encoding of speech sounds provides insight into some of the auditory

processes involved in normal communication. Auditory brainstem evoked responses (ABR)

provide more direct information about how the sound structure of a speech syllable is encoded

by the auditory system. A handful of studies have been done in similar lines to understand the

brainstem processing of speech signal (Russo, Nicol, Musacchia & Kraus, 2004; Kraus & Nicol,

2005). Based on these studies brainstem responses to a speech syllable can be divided into -

transient and sustained portions, namely the onset response and the frequency-following

response (FFR). The response functions as a gauge both of spectrum encoding and periodicity

encoding.

Lecturer in Audiology, All India Institute of Speech and Hearing, Mysore, India.



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Frequency encoding is manifested in speech-evoked auditory responses both in the

latency (Martin et al., 1997; McGee et al., 1996) and the amplitude of transient responses. The

onset responses are transient, akin to the well-documented clinical measure that uses click or

tonal stimuli as a tool for assessing both peripheral hearing and retrocochlear lesions such as

tumors of the auditory nerve or brainstem (Hall, 1992). The sustained frequency-following

response (FFR) is a phase-locked response that „follows‟ the waveform of the stimulating sound

up to a frequency of approx 1000 Hz (Hoormann et al., 1992). It must be noted that although the

FFR is a sustained response it might be considered a series of repeated transients. Thus, the FFR

can be treated as a measure of both periodicity and spectral processing.

Russo, Nicol, Musacchia and Kraus (2004) have designed a method to evaluate both the

periodicity and spectral encoding in far-field FFR recordings. The markings used in the system

are shown in the Figure.1. It contains a series of peaks ranging from peak V, A, C, D, E, F and

O. Waves V and A signal the response to the onset of sound. Wave C is thought as a response to

the onset of the vowel. Peaks - D, E and F represent vibrations of the vocal folds. The

fundamental frequency occurs at approximately 15 msec, 24 msec and 33 msec in stimulus

corresponding to wave D (22 msec), E (31 msec) and F (40 msec) in response. Neural

conduction accounts for a delay of approximately 7 ms between stimulus and response. Wave O

is a response to the cessation of sound. The small higher-frequency fluctuations between waves

D, E and F correspond in frequency to that of the first formant (F1) of the stimulus which, along

with F2, primarily shapes the vowels.

Figure.1: Depicts the wave V followed by the negative peaks A, C, D, E and F. The onset

response is bracketed while the region containing the FFR is indicated with a horizontal line

The significance of these peaks is now well established by its application in clinical

population. FFR has been used to study the brainstem coding deficits in several communication

disorders such as children with learning problems and adults with cochlear hearing loss. Some

children with language-based learning problems exhibit abnormal neural encoding of the spectral

and temporal information crucial for accurate perception of sounds (King, Warrier, Hayes &

Kraus, 2002; Cunningham, Nicol, Zecker, Bradlow & Kraus, 2001). Some also experienced

abnormal susceptibility to the demands placed on the auditory system by rapidly presented

temporal information (Wible, Nicol & Kraus, 2005).


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Khaladkar, Kartik and Vanaja (2005) suggested that using speech sounds to elicit the

ABR offers an opportunity to isolate normal speech processing from abnormal speech processing

better. The researchers further suggested that it would be useful for evaluating patients with

possible auditory processing disorders. Plyler and Ananthanarayan (2001) reported that the FFR

can encode the second formant transition in normal-hearing listeners. However, FFR encoding

seems to be severely degraded in most of the listeners with hearing loss.

Russo, Nicol, Musacchia and Kraus (2004) found that the addition of background noise

interfered with normal brainstem encoding of the speech stimulus /da/. Most affected were the

onset responses V and A which were severely degraded and completely obscured in more than

40% of the subjects. Peaks C and F however remained present in noise in most subjects. Their

peak amplitudes were also affected.

Individuals with cochlear hearing loss have consistently shown difficulties in perceiving

place (Revoile, Pickett, Holden-Pitt, Talkin & Brandt, 1987) and manner cues (Danhauer, Hiller

& Edgerton, 1984) of consonants. These difficulties increased with the degree of hearing loss.

Moore, Glasberg and Hopkins (2006) reported that subjects with moderate hearing loss

performed much worse in the difference limen for F0 compared to normally hearing subjects at

the same center frequency, suggesting that most of the hearing-impaired subjects had a poor

ability to use temporal fine structure. The temporal fine structures are important for the coding of

F0 and its harmonics.

It is very important to understand whether the individuals with cochlear hearing loss

exhibit any encoding deficits at the level of the brainstem as a result of distortion at the cochlea.

Speech-evoked brainstem responses provide a unique opportunity to explore this possibility in a

non-invasive manner. Since there is a dearth of literature on the brainstem processing for speech

stimulus in individuals with hearing loss there is a need for exploring the brainstem bases for

speech perception deficits in individuals with hearing loss. Also, there is a need to understand

whether the temporal processing difficulties in the cochlear hearing is due to the reduction in the

audibility only or does the temporal processing deficit exist even when the audibility of

stimulation is controlled. Thus to test these needs the present study was designed with the

following objectives.

Aim of the study

1. To study the effects of cochlear hearing loss on brainstem response to speech.

2. To study the effects of stimulus presentation level (equal SL and equal SPL) on

brainstem responses to speech.

Method

Participants of the present study were divided into two groups, experimental and control

group. The control group included 22 ears of normal hearing individuals aged 16-50 years and

hearing sensitivity with in 15dB HL. The experimental group included 22 ears with cochlear

hearing loss of subjects aged from 16-50 years with hearing sensitivity within 55dB HL. Speech


190

identification scores of all 22 subjects were proportional to their pure tone average of 500, 1000

and 2000 Hz. There was no abnormality indicated on click evoked ABR and the absent TEOAE

indicated the presence of cochlear pathology. The experimental group is further divided group I

(PTA >15 dB HL & ≤ 41 dB HL) and group II (PTA > 41 dB HL & ≤ 55 dB HL).

Instrumentation

A calibrated diagnostic audiometer (GSI-61) was used for estimating the pure tone

thresholds and a calibrated middle ear analyzer (GSI Tympstar) to rule out middle ear pathology.

The brainstem responses to speech and click stimuli were recorded using Intelligent Hearing

Systems (IHS Smart EP windows USB version 3.91) evoked potential systems. The Oto acoustic

emissions were recorded using Intelligent Hearing Systems (IHS Smart TrOAE windows USB

version 2.62) to check for the outer hair cell functioning.

Procedure

Stimulus used

The stimulus /da/, extensively used by Kraus and her colleagues, was used for recording

the speech-evoked ABR. A Klatt formant synthesizer (Klatt, 1980) was used to synthesize a 40-

msec speech-like /da/ syllable at a sampling rate of 10 KHz. The F0 changed from 103 to 120

Hz, F1 from 200 to 720 Hz, F2 from 1700 to 1240 Hz and F3 from 2580 to 2500 Hz. F4 and F5

remained constant at 3600 and 4500 Hz respectively. The time-amplitude waveform of the

stimulus is shown in Figure 2.

Figure 2: The wave form representation of the stimulus /da/. Fundamental frequency (F0) is seen

in periodicity of major peaks. The first formant (F1) is seen as periodically occurring smaller

peaks.

Analysis of the ABR/ FFR recordings

The peak latency and the peak to trough amplitude of Wave V, A, C, D, E, F, O were

measured. Fast Fourier Transform (FFT) was performed to obtain the information regarding

spectral characteristics of the FFR - Frequency and Amplitude of spectral peaks. FFT was

performed on all evoked potential recordings for an epoch of 15-54 ms using a custom-made

program run in MATLAB platform. The Peak amplitude corresponding to F0 and F1 region was

also calculated using a custom made program file in the MATLAB platform.

Time

Amplitude


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II. Recording of evoked potentials: The brainstem response to speech was recorded for speech

using the test protocol given in table 1.

Table 1: Stimulus and acquisition parameters used to record ABR and FFR S

tim

ulu

s

par

amet

ers

Speech stimulus /da/ (synthesized)

Duration of the stimulus 40 msec

Speech stimulus levels 40dB SL and 80 dBnHL

Polarity Alternate

Mode of presentation Ipsilateral (monaural)

Repetition rate 9.1

Acq

uis

itio

n p

aram

eter

s Transducer Insert ear phones ER-3A

Analysis time 70 msec (includes 10 ms pre-stimulus period)

Band pass filter 30 to 3000 Hz

Electrode placement Cz – Non-inverting (+ve);

Both mastoids – Inverting (-ve);

Forehead – Ground

Sweeps 1500

Electrode impedance < 10 kΩ

Inter-electrode impedance < 3 kΩ

The figure 3 represents the brainstem response to speech recorded in normal hearing

individual at 40 dBSL.

Figure 3: The recording of brainstem response to speech in a normal hearing individual at 40 dBSL

Objective Measures for Frequency Following Responses (using MATLAB platform)

The region following the onset responses was defined as the FFR. The spectral measures

performed to analyze the sustained FFR (an epoch of 15-54 ms) were the amplitude of the

spectral component corresponding to the stimulus fundamental frequency (F0 amplitude) and

first formant (F1amplitude).

The sustained portion of the responses (FFR) was passed through 100 -120 Hz and 200 to

720 Hz band pass 4th

order Butterworth filters in order to obtain the energy at fundamental

frequency and first formant respectively. The Fourier analysis was performed on the filtered


192

signal. A subject‟s responses were required to be above the noise floor in order to include in the

analysis. This was performed by comparing the spectral magnitude of pre-stimulus period to that

of the response. If the quotient of the magnitude of the F0 and F1 frequency component of FFR

divided by the pre-stimulus period was greater than one the responses was deemed to be above

the noise floor. The raw amplitude value of the F0 and F1 frequency component of the response

was then measured. This program was validated with recordings with known spectral

characteristics.


To understand the effect of cochlear hearing loss and the severity of hearing loss on the

brainstem responses to speech, the clinical group was divided into 2 groups, Group I (N = 11

ears) having PTA >15 dB HL & ≤ 41 dB HL and Group II (N = 11 ears) having PTA > 41 dB HL

& ≤ 55 dB HL. The data obtained from the groups were then compared with the control group (N

= 22 ears).

The tables 2, 3, 4 shows the mean amplitudes and latencies of the discrete peaks - waves

V, A, C, D, E, F, O and the F0, F1 amplitude for normal hearing Group I and Group II

respectively. The tables also include the results of paired sample t-test across the two

presentational levels.

Table 2: Mean, SD and t-values of the various waves latency and amplitude of brainstem

responses to /da/ at 80 dB nHL and 40 dB SL obtained in the Control group

Parameters 80 dB nHL 40 dB SL

t-values Mean SD Mean SD

Lat

ency

Wave V 8.15 0.29 9.35 0.27 11.94*

Wave A 9.09 0.31 10.82 0.42 15.07*

Wave C 19.87 0.33 21.67 0.91 8.86*

Wave D 26.66 0.58 29.15 0.84 11.60*

Wave E 37.25 0.54 39.49 0.86 10.52*

Wave F 47.35 0.48 49.64 0.69 16.07*

Wave O 56.95 0.69 59.09 0.47 12.41*

Am

pli

tude

Wave V 0.27 0.09 0.24 0.07 1.02

Wave C 0.41 0.13 0.30 0.08 3.94**

Wave D 0.48 0.12 0.33 0.12 4.43*

Wave E 0.41 0.11 0.25 0.08 4.81*

Wave F 0.44 0.13 0.34 0.11 2.58***

FF

T

F0 amplitude 30.40 7.86 24.12 7.34 2.69***

F1 amplitude 15.29 3.33 12.78 4.17 1.40

*p<0.001, **p<0.01, ***P<0.05


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Table 3: Mean, SD and t-values of the various wave latency and amplitude of brainstem

responses to /da/ at 80 dBnHL and 40 dB SL in Group I



Lat

ency

Wave V 9.23 0.76 9.81 0.73 4.69**

Wave A 10.35 0.77 10.80 0.66 3.23***

Wave C 20.61 0.95 22.03 0.95 4.29**

Wave D 28.32 1.09 29.70 1.04 3.25**

Wave E 38.93 1.12 40.09 1.19 2.59***

Wave F 48.77 0.99 49.84 0.87 2.94***

Wave O 58.12 0.78 58.79 0.53 2.67***

Am

pli

tude

Wave V 0.32 0.12 0.24 0.13 2.11

Wave C 0.28 0.13 0.24 0.10 2.34***

Wave D 0.36 0.15 0.32 0.30 1.25

Wave E 0.40 0.19 0.30 0.12 1.90

Wave F 0.30 0.16 0.27 0.15 1.29

FF T F0 amplitude 23.73 7.89 23.99 8.49 0.51

F1 amplitude 15.10 5.19 13.05 3.42 1.64

*p<0.001, **p<0.01, ***P<0.05

Table 4: Mean, SD and t-values of the various waves latency and amplitude of brainstem

response to /da/ at 80 dB nHL and 40 dB SL in Group II



Lat

ency

Wave V 10.30 0.73 9.91 0.48 3.94***

Wave A 11.57 0.98 10.83 0.76 3.80**

Wave C 22.33 0.79 23.54 1.13 2.25

Wave D 29.79 1.03 29.95 1.00 0.53

Wave E 39.86 1.07 40.97 1.26 0.76

Wave F 50.03 1.22 50.92 1.66 2.09

Wave O 58.20 0.56 58.96 0.81 2.81***

Am

pli

tude

Wave V 0.21 0.05 0.21 0.10 1.74

Wave C 0.26 0.09 0.24 0.05 0.40

Wave D 0.28 0.05 0.22 0.076 2.3

Wave E 0.23 0.08 0.22 0.05 0.69

Wave F 0.21 0.08 0.21 0.05 0.12

FF

T F0 amplitude 15.25 4.00 14.94 4.59 0.15

F1amplitude 8.90 2.28 10.03 2.53 1.4

*p<0.001, **p<0.01, ***P<0.05


194

The peaks D, E, F which are considered as the sustained brainstem responses occurred

periodically at a periodic interval of approximately 10 msec. This time period when converted

into frequency values (Frequency = 1/time period) it correlated with the F0 of the speech stimuli

(100 Hz). Russo, Nicol, Musacchia & Kraus, (2004); Kraus, Nicol, (2005) reported that the

peaks D, E, F in the sustained FFR represents the vibration of the vocal folds i.e., the F0 of the

speaker.

The results showed that this periodicity was coded effectively in normal hearing

individuals and group I (minimal to mild hearing loss). However, in group II high variability in

the standard deviation of these peaks latency and absences of identifiable responses in certain

individuals could be the indication of inaccurate coding of F0 and its harmonics.

The comparison across the presentation level revealed a significant increase in the latency

and decrease in the amplitude of the responses when the presentational level was varied from 80

dBnHL to 40 dBSL in normals for all wave parameters except for wave V amplitude. However,

Group I showed significant difference in most of the wave parameters except for the wave V, D,

E and F amplitude and Group II showed no significant difference for most of the parameters

except for the wave V, A, and O latency.

Decrease in the latency with an increase in the stimulus intensity is due to a progressively

faster rising generator potential within the cochlea and similarly faster development of excitatory

post synaptic potential (Moller, 1981). Latency of the compound action potential directly

depends on how quickly the generator potential and the excitatory post synaptic potential reach

the threshold for firing leading to reduced wave latency.

Increase in the amplitude parameters with the increase in the stimulus intensity may be

because of the increase in the audibility of the stimulus. This supports the finding by Hall (1992)

where he says that the Auditory evoke potential amplitude increases with the increase in the

intensity. The amplitude of an AER is decided by the number of neurons firing for particular

stimulus intensity. At higher intensities the number of neuron beginning to fire will be more and

amplitude of the compound action potential thus generated will be high. This had resulted in the

high amplitude evoked responses.

In the clinical group some parameters did not show a significant difference across two

presentation level because of little difference across the presentation level and this was negligible

in the group II who had higher thresholds. It could also be due to a high variability in most of the

parameters in the participants.

The F0 and F1 amplitude given in the tables clearly shows that the F0 region has the

greatest amount of response energy compared to its harmonics at both the presentation level

which is consistent with the study done by Russo, Nicol, Musacchia and Kraus (2004). They

reported that F0 region in the responses showed a greater energy compared to its harmonics. It is

due to the high energy level in the F0 region of the stimulus (Ladefoged, 1996) and also due to

the better phase locking of the lower frequencies (Gelfand, 1998).


195

Comparison between the presentation level using the paired sample t-test in normal

hearing individuals showed a significant reduction in the response amplitude in the F0 region

when the presentation level was varied from 80 dB nHL to 40 dB SL but the reduction was not

significant in the F1 region.

The reduction in amplitude may be due to the reduction in the amount of acoustic energy

reaching the neurons at 40 dB SL compared to 80 dB nHL. The clinical group revealed no

significant decrease in the F0 and F1 amplitude with the change in the presentation level. This

could be due to the little differences across the presentation level. Also, the indifference between

the low and high intensity values may attributed to the disturbed intensity processing in the

hearing loss group (Florentine, et al., 1993).

Comparison across groups at equal Sensation Levels (40 dB SL)

Kruskal-Wallis test was carried out to check whether there is any significant difference

between the three groups. The Mann-Whitney U test was carried out for those parameters which

revealed significant difference with the Kruskal- Wallis test to check whether the Groups I and II

differed significantly from that of the control group.

Table 5: Z-values between the groups at 40 dB SL

Parameters z-values

Control Vs Group I Control Vs Group II Group I & II

latency Wave V -1.12 -2.98** -0.28

Wave F -0.86 -2.09*** -1.63

Amp Wave D -0.13 -2.61** -2.39***

Wave F -1.62 -3.05** -0.41

FFT F0 amplitude -0.30 -3.25** -2.81**

F1 amplitude -0.30 -2.03*** -2.25***

*p<0.001, **p<0.01, ***P<0.05

Results of Kruskal-Wallis test for the latency and amplitude parameters of discrete peaks

and the F0, F1 amplitude revealed a significant difference between the three groups (Control

group, Group I and Group II) for the latencies of wave V and F; wave D and F amplitude; and

the amplitude of the F0. Table 5 shows the results of the Mann-Whitney U test for the pair wise

comparison of the control group, group I and group II for the latencies of waves V and F;

amplitudes of waves D and F; and amplitudes of F0 and F1.

Results of Mann Whitney U test revealed no significant difference between the group I

and the control group for all the parameters. However, there was a minimal increase in the

latency and reduction in the amplitude for the group I. This may be due to the lesser degree of

hearing loss which has minimal or no effect in the temporal processing. This is consistent with

the study done by Bus, Hall and Grose (2004). They reported that individuals with mild cochlear

impairment are minimally affected in coding temporal fine structure compared to individuals


196

with moderate cochlear impairment. Also few of the mild hearing loss individuals in their study

had near normal performance in temporal fine structure coding.

The group II revealed a significant amplitude reduction and latency prolongation when

compared with individuals with normal hearing. Also the F0 and F1 amplitude showed a

significant reduction. This could indicate reduced temporal processing in higher degree of

hearing loss. This supports the study done by Lorenzi, Gilbert, Carn, Garnier and Moore (2006)

who reported that both young and elderly subjects with moderate cochlear hearing loss

performed very poorly with temporal fine structure speech which is very important for the

coding of F0 and its formants. This loss of ability to use temporal fine structure information

perhaps was related to a loss of neural synchrony (Woolf, Ryan & Bone, 1981).

Comparison of Group I and II showed a reduction in wave D amplitude and the F0 and

F1 amplitude with the increase in severity of hearing loss. This indicated that the degree of

hearing loss has an effect on temporal processing and coding temporal fine structure of speech

(Lorenzi, Gilbert, Carn, Garnier, & Moore 2006; Moore & Moore, 2003). Effect of degree of

hearing loss on temporal fine structure coding can be understood from the study done by Bus,

Hall and Grose (2004). Their data revealed that individuals with mild cochlear impairment are

minimally affected in coding temporal fine structure compared to individuals with moderate

cochlear impairment. Also a few of the mild hearing loss individuals in their study had near

normal performance in temporal fine structure coding.

Overall we can conclude that though the audibility of the stimulus was same across the

three groups, still the clinical group had some deficit in coding information at the auditory nerve

which was reflected in the latency and amplitude measures. The minimal to mild hearing loss

group had minimal loss of information and were almost similar to the normal group. This deficit

was more pronounced in the moderate hearing loss group.

Comparison across the groups at equal Hhearing levels (80 dB nHL)

Results of the Kruskal-Wallis test revealed significant difference between the 3 groups

for all parameters except for the wave V amplitude. Table 6 shows the results of the Mann-

Whitney U test for the pair-wise comparison of all parameters for between the groups. Results of

Man Whitney U test showed a significant difference between the group I and control group for

most of the parameter except the Wave E amplitude, F1 amplitude. As expected the normals had

shorter latencies and higher amplitude of the peaks compared to the Group I. This is due to

higher audibility in normal hearing individuals compared to group I. Also, there was a significant

reduction in the F0 amplitude in the group I. Though F1 amplitude showed a slight reduction in

amplitude in Group I it failed to show any significant difference.

In group II the wave latencies increased and the amplitude reduced significantly in the

compared to control group. Also, there was a drastic reduction in the F0, F1 amplitude. This

suggests that the inadequate audibility would affect the temporal processing to a great extent in

moderate hearing loss group.


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Table 6: Z-values between the groups at 80 dB nHL

Parameters z-values

Control Vs Group I Control Vs Group II Group I Vs Group II

Latency

Wave V -3.46** -3.93* -1.96

Wave A -3.58* -3.95* -2.49***

Wave C -2.21*** -4.07* -3.11**

Wave D -3.88* -3.99* -2.73**

Wave E -2.83** -4.14* -1.53

Wave F -3.54* -4.04* -1.98***

Wave O -3.63* -3.76* 0.00

Amplitude

Wave C -2.58*** -2.95** -0.20

Wave D -1.98*** -3.82* -1.11

Wave E -0.591 -3.36** -1.87

Wave F -2.16*** -3.70* -1.24

FFT F0 amplitude -2.36*** -4.27* -2.74**

F1 amplitude -0.53 -3.57* -2.60**

*p<0.001, **p<0.01, ***P<0.05

Comparison between group I and group II revealed increase in the latency and decrease

in the amplitude of all parameters though significant difference was seen only for wave A, C, D,

F latency. A significant reduction in F0, F1 amplitude was also seen in group II. This again

shows that as the hearing loss increases the audibility reduces and this would have affected the

temporal processing and F0, F1 coding.

Conclusion

To conclude the comparison across the groups at equal hearing level were done in order

to see the kind of difficulties that the hearing impaired individuals will face in day to day

situation. As we know that in day to day situation both normal and hearing impaired individuals

will be exposed to sounds at equal hearing levels and not equal sensation level. From the results

above it is clear that as the degree of hearing loss increases the temporal processing degrades due

to reduced audibility or could be due to the altered physiology of the inner ear. Thus, in day to

today situation hearing impaired individuals might miss out lot of the temporal cues which

essential for the speech perception. The cochlear hearing loss individuals will most often have

degraded coding of F0 and its harmonics and this is more pronounced for a higher degree of

hearing loss.

From this we can conclude that as the degree of hearing loss increases the ability to

process temporal fine structure of speech degrades, thus, compromising the speech intelligibility

in quiet as well as in adverse environments.

Clinical implications

1. Brainstem responses to speech syllables can throw more light to understand the role of

brainstem processing of speech sounds.


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2. FFT analysis of the brainstem responses is a useful tool in detecting deficits in speech

sound processing. Amplitudes of F0 and F1 peaks proven to be useful for this type of

evaluation.

3. It can be used as an objective tool to assess temporal processing in difficult to test

population.

4. It can also be used as a tool for hearing aid selection or to check for benefit from hearing

aid or rehabilitation.

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Music Processed by Hearing Aids

Sushmit Mishra & P Manjula

Abstract

The processing of music by hearing aids is a challenge which the hearing aid industry is

facing today. The present study is an attempt to study the hearing aid processed music while

changing different parameters of the hearing aid. Thus through a controlled study design the

parameters in a hearing aid appropriate for good music perception were evaluated. The

evaluations were done using the spectral measurement and subjective perception of the music

samples processed by hearing aids programmed with different parameters.

The recorded music samples were subjected to perceptual analysis of five parameters on

a five-point rating scale and objective analysis was done using spectral slice in Praat software.

The results of objective and subjective analysis implied the following settings of the parameters

in the digital hearing aid to be more appropriate for the music sample studied. All these

conclusions are made with reference to the music samples, hearing aids and settings that were

used in the study. A fifteen channeled hearing aid was better for music perception than a six

channeled hearing aid. Further, the knee-point for ideal music perception should be set as high

as possible till it is not uncomfortable for the subject, feedback management and the noise

cancellation system should be turned off.

Key words: spectral measurement, music perception, compression knee-point, Noise

cancellation, feedback management

Introduction

Music is an important and enjoyable part of life for people of all ages. It has been found

to release tension, raise spirits and promote a feeling a well-being. There are just a few people

who do not enjoy listening to music but there are many people who regard music as one of their

chief pleasures. Music is an important ingredient of every culture throughout the world as a form

of entertainment and as a form of an art.

Following the perception of speech the appreciation of music is the next commonly

expressed requirement by the users of cochlear implants (Stainsby, McDermott, McKay & Clark

1997). This may well be said for the individuals who use hearing aids also. When the individuals

who enjoy listening to music acquire hearing impairment one might expect a significant effect on

music perception and the pleasure derived from music. Although there may be some restoration

of hearing through the use of hearing aids, it is questionable whether most hearing aids process




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music in such a way as to enable the user to hear and enjoy music to the same degree as prior to

acquiring hearing loss.

The reason that individuals with hearing impairment fail to perceive or appreciate the

sound quality of music is because the hearing loss has differential effects on frequency

selectivity, temporal resolution, loudness perception/intensity discrimination and suprathreshold

performance. These contribute to the difficulty of the individuals with hearing impairment to

perceive or appreciate music (Chasin, 1996).

There is a dearth of research in the field of music and hearing impairment. This is also

because the musicians and the scientists often use different terminologies in describing the

characteristic of a tone. For example, a researcher may say 440 Hz tone and a western musician

may denote it by „A‟. The musicians are particularly interested in the tones below „C‟, i.e. 262

Hz. But most audiologists would ignore the sound energy below 250 Hz because of the poor

signal-to-noise ratio and because of hearing assessment problems. But for musicians this low

frequency information can significantly contribute to the quality judgment (Chasin, 2003).

Speech tends to be a well controlled spectrum with well established and predictable

perceptual characteristics. In contrast music spectra are highly variable and the perceptual

requirement can vary based upon the musicians, type of music and the type of instrument being

played. There are five major differences between speech and music stimuli as reported by Chasin

(2003 & 2006) and Chasin and Russo (2004). They are (i) the long-term average spectrum of

music vs. speech (ii) differing overall intensities (iii) crest factors (iv) phonetic vs. phonemic

perceptual requirements and (v) difference in loudness summation and loudness intensity.

Unlike the long-term average spectrum of speech, music is highly variable and a goal of a

long-term average music spectrum is poorly conceived. The potential intensity range for speech

is quite restricted, approximately 30 to 35 dB. But the dynamic range of music is of the order of

100 dB. A typical crest factor with speech is about 12 dB. Crest factors of 18 to 20 dB are not

uncommon for many musical instruments. The perceptual need for speech is quite clear. But for

music the perceptual need is quite varied and depends upon the instrument being played. The

vocal cords function as half wave resonators whereas the musical instrument can be half wave

resonator or quarter wave resonator depending upon the instrument which is played. These

differences make it difficult for a hearing aid user to enjoy music with a hearing aid that is

mainly designed for speech.

Historically the primary concern for the hearing aid design and fitting is the optimization

for speech input (Chasin & Russo, 2004). Musicians with hearing loss have often complained

about the poor sound quality while they are playing or listening to the music through their

hearing aid (Chasin, 2003). Not only the technology for music input in hearing aids is in its

infancy but the research and clinical knowledge of what the musicians and those who like to

listen to music need to hear is also in the early stage of understanding (Chasin & Russo, 2004).

Presently, the digital technology is replacing the analog technology used in the hearing aid

industry. The digital technology has the advantage of employing various algorithms such as


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adaptive noise-reduction systems, adaptive directionality, adaptive feedback suppression and

highly flexible control of numerous amplification characteristics including complex forms of

compression. Digital technology is also enabling the processing of sounds in different channels

having different compression settings. Chasin (2003, 2006) recommended a set of parameters

being ideal for the perception of music through the hearing aids. Thus, through a controlled study

design the parameters in a hearing aid ideal for music perception need to be evaluated.

The present study is an attempt to evaluate the hearing aid processed music while

changing different parameters of the hearing aid. Thus, the objectives were as follows:

1. To compare the processing of music by using a six-channeled and a fifteen-channeled

hearing aid where all the other parameters of signal processing of the hearing aid are kept

the same.

2. To compare the music processed in a six-channeled hearing aid with

a. the compression knee-point being set high than that optimized for speech for a

particular hearing loss

b. by enabling and disabling the noise reduction system

c. by enabling and disabling the feedback management system

Method

The efficacy of the hearing aids was evaluated using the subjective perception and

objective spectral analysis of the music samples processed by the hearing aids.

Participants

Three groups of participants participated in this study, namely, Group I (Non-musicians

group), Group II (Musicians-Singers group) and Group III (Musicians-Instrumentalists Group).

They had hearing sensitivity within normal limits with no significant history of external or

middle ear infection or malformation of the ear.

Group I (Non-musicians group):15 participants with no formal education in music were

considered. The age of the participants ranged from 18 to 25 years (mean age of 20.75 years). It

was ensured that all the participants selected in the study enjoyed listening to music.

Group II (Musicians-Singers group): 15 participants with at least 10 years of experience in

professional singing were selected. The age range of the participants was from 24 years to 59

years (the mean age of 39.90 years). The average experience with professional singing in this

group was 24.8 years (range being 10 to 39 years). In order to have homogeneity in the group

care was taken to see that all the participants were practicing the Carnatic style of singing.

Group III (Musicians-Instrumentalists Group): 10 participants were selected in this group.

All the participants were practicing „Odissi‟ style of playing the instrument. Three of the

instrumentalists played sitar, two of them played the flute, three played the sarod and the other

two played the veena. The age range of the participants was between 36 and 52 years (mean age


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being 48.10 years). The average experience in professional music for this group was 27.2 years

(range being 24 to 32 years).

Instruments used

Hearing Aids: Two commercially available digital Behind-The-Ear (BTE) hearing aids were

used in the study. The first hearing aid (Hearing aid A) was a six-channeled hearing aid and the

second hearing aid (Hearing aid B) was a fifteen-channeled hearing aid. These two hearing aids

were selected because, apart from the number of channels, the signal processing strategy, the

microphone technology and the noise canceller were technically similar. Both the hearing aids

used wide dynamic range compression (WDRC), dynamic noise canceller (dNC), feedback

management system and an omni directional microphone technology. Both these hearing aids

had an option of switching off the noise cancellation system and the feedback management

system.

Computers and Hi-Pro: A personal computer installed with NOAH (3.0 version) software and

connected with Hi-Pro were used to program hearing aids. Two laptops operating on Windows

XP and Praat software were also used in this study for recording the music sample. Frontech

speakers, 340 Watt PMPO were connected to the laptop that played the music. The volume was

set at a comfortable loudness level. The music samples were recorded on another laptop using

the Praat software. These samples were later transferred to an audio compact disc. The sampling

rate used in all the recording of the study was 32 kHz. The music samples were played to the

listeners from a laptop through the head phones (Fontopia MDR-EX51LP Consumer

Headphones) using the Praat software.

Coupler: A 2 cc coupler (HA-2) was used for coupling the hearing aid to the microphone while

recording.

Microphone: An omni directional microphone was connected to the laptop computer. This

microphone was in turn attached to the coupler using „fun tak‟ to record the output from the

hearing aid on the laptop using the Praat software.

Music Sample: A music sample recorded on an audio compact disc was used. Carnatic music

which was being played instrumentally was selected. The music sample had the lead music

played by violin and the other instrument being played was the mrudhagam. The music sample

was chosen from the music album titled „lagudi‟ and the music was based on raaga „Mohana

Kalayani‟. 90 second duration of the sample was selected for the purpose of evaluation.

Room Setting: A sound treated air conditioned room was selected for recording the music

sample from the hearing aids. The ambient noise levels inside the room were within permissible

limits.

Procedure: For the purpose of the study, the study was divided into 4 stages:

Stage 1: Recording of the hearing aid processed music samples

Stage 2: Programming of the hearing aid

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Stage 3: Subjective analysis of the music samples

Stage 4: Measurement of spectra of the music samples

Stage 1: Recording of the Hearing Aid Processed Music

For the comparison of the effect of channels on processing of music, two digital hearing

aids were taken; one comprising of 6 channels (Hearing aid A) and the other comprising of 15

channels (Hearing aid B). The knee-point of both the hearing aids was at 54 dB when

programmed for the speech in quiet (default program). The knee-point was raised by 18 dB to

make it 72 dB. The music samples were recorded with noise cancellation and feedback

management systems off. Apart from the difference in number of channels the other signal

processing parameters in the hearing aids were similar.

A sample was recorded from the fifteen channeled hearing aid (Hearing aid B) with knee-

point set at 18 dB higher than the default knee-point setting for the speech as recommended by

the first fit of the programming software. This time both the noise cancellation system and the

feedback management system were turned on.

For recording the other music samples a 6-channeled digital hearing aid (Hearing aid A)

was selected. Music sample was played to the programmed hearing aids. The hearing aid

processed music was recorded. During recording of different samples the hearing aid A was

taken and the hearing aid processed music was recorded in each of the following conditions:

knee-point set at 72 dB with both the noise cancellation system and feedback management

systems switched off initially. Then, a music sample was recorded with the high knee-point (i.e.,

72 dB) with the noise cancellation system on and the feedback management system off. Later

another music sample was recorded with the knee-point being high (i.e. 72 dB) with the feedback

management system on and the noise cancellation system off. Finally, a music sample was

recorded with the noise cancellation system and feedback management system being switched on

with the knee-point being high (i.e., 72 dB).

On the whole there were eight music samples; two from the fifteen channeled hearing

aid, five from the six channeled hearing aid and the original music sample recorded through the

coupler. They are given in the following Table 1.

Thus, the recording of the music sample without and with the hearing aid was done.

These eight recorded music samples were later used for the subjective ratings and the spectral

analysis. The music sample was played using Praat software from a laptop through the speakers.

The hearing aid was placed at equivalent distance of 5 cm from either of the speakers and at 900

Azimuths, as shown in the figure. A foam sheet was placed below the hearing aid so that it did

not pick-up any noise due to vibration of the table. It was taken care that the microphone of the

hearing aid was at the level of centre of the speakers. The digital hearing aid was connected to a

HA-2 (2 cc) coupler which in turn was connected to the recording microphone. The recording

microphone was connected to the lap top computer for recording the music sample using the

Praat software. All the recordings in Praat software were made using 16 bit mono recording.


205

Thus, the music processed by the hearing aid in each of the seven different programmed settings

of the hearing aids was recorded.

Table 1: The eight music samples recorded with different settings of the hearing aids

Music samples Conditions of recording

Sample 1 Original music sample recorded through 2 cc coupler

Sample 2 Hearing aid B with knee-point high, noise cancellation and feedback

management off

Sample 3 Hearing aid A with knee-point high, noise cancellation and feedback

management off

Sample 4 Hearing aid B with knee-point high, noise cancellation and feedback

management on

Sample 5 Hearing aid A with knee-point high, noise cancellation and feedback

management on

Sample 6 Hearing aid A with knee-point at default, noise cancellation and feedback

management off

Sample 7 Hearing aid A with knee-point high, noise cancellation on and feedback

management off

Sample 8 Hearing aid A with knee-point high, noise cancellation off and feedback

management on

In order to make all the music samples equivalent, the original music sample was also

played in the same condition and recorded through the coupler to make the unprocessed music

sample equivalent to the music sample processed through the hearing aids. The music samples

were not normalized. The samples were then transferred to an audio compact disc.

Stage 2: Programming of the Hearing Aid

The hearing aids were programmed for a hypothetical flat sensorineural hearing loss with

air conduction threshold being 50 dB HL at all the audiometric frequencies. A flat hearing loss

was used so that the compression characteristic, when tested, remained same across all the

frequencies. The digital hearing aid was connected through a Hi-Pro to the personal computer

(PC) with software for programming. After the hearing thresholds were fed into the software

(NOAH 3.0) the digital hearing aids were programmed based on the NAL-NL1 prescriptive

procedure in the hearing aid programming software. An acclimatization level of 2 was used

while programming.

Stage 3: Subjective analysis of the music samples

Measures of quality judgment of the music samples were obtained using five, five-point

perceptual rating scales that was relevant to music. This is a modification of the work of

Gabrielsion and Sjogren (1979) that has been used extensively in the hearing aid industry

(Chasin & Russo, 2004). The participants were asked to rate the music samples on the perceptual


206

parameters of loudness, fullness, crispiness, naturalness and overall fidelity. Participants were

given the following definitions of the five perceptual parameters (Chasin & Russo, 2004).

Loudness was defined as the music that is sufficiently loud in contrast to faint, ranging

from 5 to 1 on the rating scale. Fullness was defined as the music being full in contrast to thin,

ranging from 5 to 1 on the rating scale. Clearness was defined as the music being clear and

distinct in contrast to being blurred or diffused, ranging from 5 to 1 on the rating scale.

Naturalness being defined as the music seems to be as if there is no hearing aid and the music

sounds as “I remember it”, ranging from 5 to 1 on the rating scale. Overall fidelity being defined

as that the dynamics and range of the music is not constrained or narrowed, ranging from 5 to 1

on the rating scale.

Specifically, the participants were asked to rate from 1 (poorest) to 5 (best) on the following

perceptual scales: loudness, fullness, crispiness, naturalness and overall fidelity. Thus, a perfect

perceptual reproduction score was 25 considering all the five parameters on the scale. The scales

for rating on the five parameters were as follows:

1. For loudness: 1 ( faint)……………….5 (sufficiently loud)

2. For fullness: 1 (thin)………………5 (full)

3. For clearness: 1 (blurred)………………5 (distinct and clear)

4. For naturalness: 1 (unnatural)……………...5 (natural)

5. For overall Fidelity: 1 (restricted)………………5 (wide and not constrained)

The music samples were played from a computer using the Praat software through the

head phones (Fontopia MDR-EX51LP Consumer Headphones). The participants were instructed

to listen to the samples at their comfortable loudness level.

All the participants in the three groups were made to listen to the music samples in

similar conditions. A relatively quiet room away from traffic noise and other noises was selected.

Each subject was made to listen to the eight different music samples mentioned above.

Instruction: The participants were given an identical set of instruction in a written format, in

English, so that the instruction for all the participants remained essentially the same. Four

participants in Group III asked for instruction written in Oriya, hence a translation of the

instruction were done which was verified by two graduate students in Oriya for the correctness

of the meaning. The instructions were further clarified by the experimenter before the

participants rated the music sample, if required. It was made certain that the participants were

absolutely clear with the terminology and completely certain about the rating scale before they

rated the music samples.

Stage4 - Measurement of spectra of the music samples

The selected music sample, from the recorded music samples, as processed by the

hearing aid were subjected to spectrum analysis using the Praat software. For the precise

comparison equivalently paired music slices were taken from the eight music samples. In each of

the samples recorded the samples for analysis were taken at the interval of 14 to 24 seconds, 48



207

to 58 seconds and 74 to 84 seconds. Three ten-second duration of the music samples were

selected for analysis with Praat software as the Praat software could analyze the music sample of

less than 10 second duration. Spectral analysis of three ten-second duration of the music samples

was obtained in the Hammin window. The energy concentration at octave and mid-octave

frequencies (from 200 to 8000 Hz) was measured and tabulated.

Results

The main objective of the study was to compare the processing of music through different

hearing aid settings, subjectively using a rating scale and objectively using the spectral analysis.

Subjective Analysis

For the subjective analysis the samples were first presented to 40 listeners to be rated on a

rating scale. There were a total of eight music samples. Details of these samples are provided in

Table 1. The original music sample and seven hearing aid processed music samples were rated

on a five-point rating scale. These ratings were tabulated. The statistical analysis was carried out

with the help of the Statistical Package for the Social Sciences (SPSS, Version 10). The non-

parametric test was used in the statistical analysis. The data, in terms of the five parameters, were

analyzed for the comparison of the three groups of participants using Kruskal-Wallis test (Non-

parametric equivalent of one-way ANOVA). Mann-Whitney U test was used to see the pair-wise

difference between the groups, where the comparisons were made taking two groups at a time.

Later, the original music sample was compared with all the other music samples using the

Wilcoxon Signed Rank test. These analyses were repeated for all the five parameters.

The Kruskal-Wallis and Mann-Whitney U Test was applied to all the parameters in the

rating scale. It revealed that the there was a significant difference (p<0.05) between the ratings

given by the non-musicians and singers, and the non-musicians and instrumentalists. But the

rating given by the singers and the instrumentalist group was not significantly different (p>0.05).

Wilcoxon signed rank test revealed that the non-musicians rated the music sample recorded from

the fifteen channeled hearing aid with the noise reduction system and feedback management

system (sample 2) to be similar to the original music sample (p>.05). It was interesting to note

that the instrumentalist and the singers group rated the sample 2 to be similar to the original

music sample in three parameters of perceptual rating but rated it to be different in two

parameters, namely, naturalness and overall fidelity.


208

Spectral Analysis

The result of analysis of the objective measures was similar to subjective measures.

Frequency (Hz)

60004000300020001000500250

Inte

nsity

(dB

SPL)

40

20

0

-20

-40

-60

Samples

Sample 1

Sample 2

Sample 3

Sample 4

Sample 5

Sample 6

Sample 7

Sample 8

Fig. 1: Hearing aid output at different fqs for different samples, in 48 to 58 seconds interval

Note: All the values in the graph are referenced to 2.10-5

dyne/cm2

Since on the Praat software a sample of maximum 10 seconds could be analysed, the

sampling for each music sample was done at intervals of 12 to 22 seconds, 48 to 58 seconds and

74 to 84 seconds. The energy concentration at each of octave and mid-octave frequency was

measured and was plotted as graphs as shown in Figure 1. All the three figures showed similar

pattern and Figure 1 represents the sample in the interval 48 to 58 seconds.The descriptions of

the music sample are given in Table 1. From the figures it is evident that the music sample 2

(Hearing aid B with knee-point set high, noise cancellation system and the feedback management

system turned off) gave the best representation of the original music sample. The music sample 3

(Hearing aid A with knee-point high, noise cancellation and feedback management off) and

music sample 4 (Hearing aid B with knee-point high, noise cancellation and feedback

management on) gave the second and third best representation of the original music sample

respectively. From the graph, it was evident that activation of the noise cancellation system or

the feedback management system in the hearing aids led to degradation of the sample in terms of

reduction of energy level in the low frequencies and increase of energy level in mid- and high-

frequencies.

From the figure, it was evident that the outputs from the hearing aids were lower than the

original in the lower frequency. But from the mid-frequency, around 1 KHz to 4 KHz, the

hearing aid amplified the music. The activation of the feedback system and noise cancellation

system (Sample 4, 5 & 8) led to a reduction of energy at the frequency about 2 KHz which is

evident as a dip in the energy output. It is quite evident from the graph that the output through

hearing aid B gave a better representation of the original music.

Discussion

The perception of music is dependent on various factors such as the relationship of the

harmonics in the lower frequency fundamentals and the higher frequency harmonics, the

concentration of energy in the lower frequency, the temporal resolution of the music in the ear in


209

order to be judged as good in quality. Hence the objective spectral evaluation of the output alone

will not provide a clear picture of the quality of music processed by a hearing aid. The finding

from the objective study should be complimented by a subjective study. A perceptual rating

inherently has many factors which are dependent on the subject. The experimenter has limited or

no control over the subject-dependent factors such as motivation, understanding and bias of the

participants. Hence the study evaluated the music samples processed by hearing aids both

subjectively and objectively.

Integration of the Subjective and Spectral Analysis

All the eight music samples recorded through the hearing aid were given a poorer rating

subjectively by all the listeners. In the studies done earlier hearing aid users have always

preferred a lower cut-off frequency in judgment of the quality of music (Punch, 1978; Frank &

Hall, 1985). Chasin (2003) noted that the information in the low frequencies contributed

significantly to the quality judgment of music. The figures depicting the hearing aid output at

different frequencies for different samples revealed that neither the hearing aid A nor the hearing

aid B represented the original music well in the lower frequency region. The output of the

hearing aid was always poorer than the original music sample in the lower frequency region and

the hearing aids were able to amplify the music after a frequency of around 1 KHz. Mishra and

Abraham (2007) have also noted that overall music processed through the hearing aids showed a

poor representation of waveform in the low frequencies. It can be noted that the sample in which

the hearing aids provided a good representation of the music in the lower frequency are rated

higher by the listeners. The figures depicting the original music showed a concentration of

energy in the lower frequency region and the energy falling precipitously after a frequency of

500 Hz. All the subjective/perceptual ratings indicated a much higher rating for the original

music sample which had relatively higher energy in the low frequency region.

Further, it was seen in this study that the hearing aid B having 15 channels represented

the original music better on perceptual rating with the knee-point being set higher. The

observation of the figures which represented the output from the hearing aid also depicted that

the output from the Hearing aid B having the knee-point raised to 72 dB (Sample 2) gave better

representation of the original music sample (Sample 1) than Hearing aid A with similar settings.

Hearing aid A with the knee-point raised to 72 dB (Sample 3) followed the output from the

Hearing aid B. In the perceptual rating too the ratings given to the hearing aid B, with the knee-

point high and the noise cancellation and feedback management off, was not significantly

different from the original music.

The rationale for having a single channel or double channel hearing aid is to have equal

compression ratio across the entire frequency range remains equal so that the ratio of the energy

in the low frequency and the high frequency remains essentially the same. According to Chasin,

and Russo (2004) if there is an imbalance in the amplification in the low frequencies and the

high frequencies the timbre will be affected.


210

Chasin (2003) noted that for wood wind instruments and quieter music or for clients with

precipitous sloping audiometric configuration, a multi-channel hearing aid may be acceptable,

since for the wood wind instruments the perceptual reliance is on the information in the lower

frequencies. But the music sample selected in the present study was not produced by any wood

wind instrument and the lead instrument was violin.

Chasin and Russo (2004) had noted that some musical instruments like piano and violin

are more speech-like. Such instruments are half wave resonator with evenly spaced harmonics.

Since the lead instrument in the music sample in the present study was violin this may be a

reason why a fifteen channel hearing aid performed better than a six channeled hearing aid. It has

been noted in various studies that multi-channel hearing aids improve speech perception

(Mispagel & Valente, 2006).

The increase in the number of channels leads to different gain and compression setting in

different frequency bands and there is disturbance between the low frequency fundamentals and

the high frequency harmonics. In the analysis of the subjective results of the Group I (consisting

of individuals not having any experience in professional music) there was no significant

difference between the original music and the out put from the hearing aid B with knee-point

raised by 18 dB. However, participants in Group II and Group III (consisting of professional

singers and instrumentalists) rated the music sample 2 to be similar to that given to the original

music sample, except in two parameters in the perceptual rating, namely, the naturalness and

overall fidelity. The differences in naturalness and reduced overall fidelity may be attributed to

the disruption of ratio or balance of the low frequency fundamental and the high frequency

harmonic structure. Such a difference was not perceived by the Group I who indulged in

listening to music just to seek pleasure. The variation may also be too subtle to be picked up an

untrained listener. This draws attention to the fact that special care should be taken while

prescribing hearing aids to the trained musicians as the demand of the musicians is far greater

than the non-musicians who just appreciate music.

Chasin (2006) had recommended that the knee-point of the hearing aid should be set

around 65 to 75 dB and the compression ratio should be low (e.g. 1.5:1). In the present study the

knee-point of the hearing aid was set at 72 dB. The knee-point while programming the hearing

aid was 54 dB which was the knee-point setting for speech as suggested by first fit of the

software. The subjective rating showed that the listeners had a preference for the hearing aid

output where the knee-point that has been set to higher level for both the hearing aids (Sample 2

& 3). The graph obtained for the outputs of the hearing aid in different settings also showed that

setting the knee-point higher gave a better representation of the music in the lower frequency

region. When the knee-point was set at the default setting for speech, the output of the hearing

aid B was much lower in intensity in the low frequency region (Sample 6). On raising the knee-

point the output obtained from the hearing aid A was better compared to the default setting.

All the participants gave poorer rating to the music samples in which the noise

cancellation system was activated (Sample 4, 5 & 7). In the graphs depicting the output from the


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hearing aid in different settings it was noted that whenever the noise cancellation system was

activated it led to suppression of energy in the low frequency region. For time invariant noise,

the noise cancellation system in the present day hearing aids assume that since most of the noise

power is concentrated in the low frequencies, the speech is masked in this frequency region and

filtering out both speech and noise over this frequency range will have little or no effect on

intelligibility but will reduce the loudness and annoyance of the noise; i.e., overall sound quality

will be improved (Levitt, 2001).

The long-term spectra of noise and speech reveal the difference between speech and

noise in their concentration of energy. Hence, it can be assumed that the hearing aids used in this

study were assuming the music sample to be a time invariant noise and hence there was a

cancellation of energy in the low frequency region. As discussed previously the concentration of

energy in the low frequency region is essential for the judgment of quality of music to be better.

The findings of this study support that by Chasin (2003 & 2006), Chasin, and Russo (2004) and

Mishra, Kunnathur and Rajalakshmi (2005). The previous studies have noted that there is high

probability for the hearing aid to confuse music for noise and hence had recommended

deactivation of the noise cancellation system.

The activation of the feedback management system led to low energy levels which in turn

led to poorer rating by all the participants. In the figures it was noted that whenever the feedback

management system was activated (Samples 4, 5 & 8), it led to a dip at the frequency region of

around 2 KHz. In notch filtering of the feedback management system it is possible to invert a

band pass filter and remove the part of the peak in frequency response. It generally removes a

narrow part of the spectrum centered on the frequency of the filter. This type of filtering is used

to counter the acoustic feedback where the notch is tuned to remove a narrow band of frequency

around the offending frequency (Agnew, 1993). Most probably the activation of the feedback

system led to employment of such a filter which nullified the gain at a frequency range centered

around 2 KHz. Suppression of energy in a particular frequency will have a deleterious effect on

music perception since the gain should be equal and balanced over the frequency region for the

optimal perception of music.

The simultaneous activation of the noise cancellation system and the feedback

management system led to greater deleterious effect on the perception of music both objectively

and subjectively (Sample 4 & 5). It was worth noting that the hearing aid A had far more

deleterious effect when both the noise cancellation system and the feedback management system

were activated than hearing aid B by comparing outputs of sample 4 and sample 5 on the spectral

analysis.

Mishra, Kunnathur and Rajalakshmi (2005) noted that directional system leads to

significant loss of low frequency sound which may remove valuable information for music.

Hence, they recommended an omni-directional hearing aid for better perception of music. Even

though the hearing aids (Hearing aid A and Hearing aid B) in the present study had an omni-


212

directional microphone, the output in the low frequency was reduced, may be because of the

activation of the noise cancellation.

Conclusions

The hearing aid processed music samples were subjected to perceptual analysis of the

five parameters on a five-point rating scale. An objective spectral analysis was also done using

spectral slice in Praat software. The results of objective and subjective analysis implied the

following settings of the parameters in the digital hearing aid to be better for music perception.

All these conclusions are made with reference to the music samples, hearing aids, settings that

were used in the study.

A fifteen channeled hearing aid was better than a six channeled hearing aid for music

perception

The knee-point for ideal music perception should be set as high as possible till it is not

uncomfortable for the subject

The feedback management and the noise cancellation system should be turned off

In conclusion it can be said that music perception through the hearing aid can be

optimized to a greater extent with appropriate changes in the parameters of the hearing aids. It

was found from the results of the present study that a hearing aid with 15 channels (compared to

6 channels) disabling the noise cancellation and feedback management system would improve

the perception of music appreciably. The experimenters quite agree with Chasin (2003) who

noted that “a hearing aid ideal for music perception can be programmed to have good speech

intelligibility but the vice-versa is not true”.

References

Agnew, J. (1993). Applications of notch filter to reduce acoustic feedback. The Hearing Journal,

46 (3):37-40, 42-43.

Chasin, M. (1996). Musicians and the Prevention of Hearing Loss. San Diego: Singular

Publishing Group.

Chasin, M. (2003). Music and hearing aids. The Hearing Journal, 56 (7), 36-41.

Chasin, M. (2006). Hearing aids for musicians. The Hearing Review, 59 (3): 7-11.

Chasin, M. & Russo, F.A. (2004). Hearing aids and music. Trends in Amplification, 8 (4), 35-47.

Franks J.R. & Hall T.C. (1985). Hearing aid wearers and music. The Hearing Journal, 38 (5),

14-16.

Gabrielsson A. & Sjogren H. (1979). Perceived sound quality of hearing aids. Sand. Audiology,

8, 159-169


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Levitt, H. (2001). Noise cancellation in hearing aids: An overview. Journal of Rehabilitation

Research and Development. 38 (1), 111-121.

Mispagel K. M. & Valente M., (2006). Effect of multichannel digital signal processing on

loudness comfort, sentence recognition and sound quality. Journal of American Academy

of Audiology. 17 (10), 681-707

Mishra, S.K., Kunnathur, A. & Rajlakshmi, K. (2005). Hearing aids and music: Do they mix?

Indian Speech and Hearing Association Conference, Indore.

Mishra, S. & Abraham A.K., Processing of Music by Hearing Aids (2007) Frontiers of Research

in Speech and Music, Mysore.

Punch J.L. (1978). Quality judgments of hearing aid- processed speech and music by normal and

otopathologic listener. J. Am. Aud. Soc. 3, 179-188.

Stainsby, T.H., McDermott H. J., McKay C. M. & Clark G. M. (1997). Preliminary results on

spectral shape perception and discrimination of musical sounds by normal hearing

subjects and cochlear implantees. Proceedings from the international conference on

computer and music.


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Efficacy of Frequency Transposition Hearing Aid

In Dead Region Subjects

Swapna Raj S & K. Rajalakshmi

Abstract

A hearing aid is an electroacoustic device which enables a hearing impaired individual

to make maximum use of his residual hearing. Decreased audibility, reduced dynamic range,

decreased frequency resolution and temporal resolution are common problems in individuals

with sensorineural hearing loss. Sensorinueral hearing loss is also commonly called cochlear

loss, inner ear loss and nerve loss. The sensory mechanism comprises of the Outer hair cells

(OHC‟s) and the inner hair cells (IHC‟s). Damage to OHCs will lead to a reduction in the

compressive mechanism of the cochlea. Damage to IHCs will lead to a reduction in sound

transduction process. For this reason such regions are referred to as “Dead regions”. Steeply

sloping hearing loss is often associated with cochlear dead regions and also high frequency part

of speech contributes no information in such individuals. Thus, it is essential to transpose high

frequency information to the useful hearing at low frequencies in order to make high frequency

information accessible. Hence, the present study aimed at evaluating 10 subjects (15 ears) with

Dead regions. Subjects who were diagnosed as having dead regions using Modified Threshold

Equalising Noise (TEN) test participated in the study. Frequency transposition hearing aid was

fitted for individual who have dead region. Speech identification performance was evaluated

with High frequency sentence and word list in Transposition and No Transposition conditions.

The results revealed that with frequency transposition there is statistically significant amount of

benefit than non transposed condition for individuals with steeply sloping hearing loss with dead

regions.

Key words: High frequency sensorineural hearing loss, Frequency transposition, Dead region,

hearing aids, TEN.

Introduction

A hearing aid is an electroacoustic device which enables a hearing impaired individual to

make maximum use of his residual hearing. It takes an acoustical signal such as speech and

converts into an electric signal before amplification stage. The primary goal is to amplify and

deliver speech and other sounds at levels equivalent to that of normal speech and conversation.

It is the most effective therapeutic approach for the majority of individuals with hearing loss. It

differs in design, size, gain, ease of handling, volume control and availability of special features.

Decreased audibility, reduced dynamic range, decreased frequency resolution and

temporal resolution are common problems in individuals with sensorineural hearing loss.

Sensorinueral hearing loss is also commonly called cochlear loss, inner ear loss and nerve loss. Reader in Audiology, All India Institute of Speech and Hearing, Mysore, India; e-mail: [email protected]


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The sensory mechanism comprises of the Outer hair cells (OHC‟s) and the inner hair cells

(IHC‟s). Damage to OHCs will lead to a reduction in the compressive mechanism of the cochlea.

Damage to IHCs will lead to a reduction in sound transduction process. For this reason such

regions are referred to as “Dead regions” by Moore and Glasberg, (1997), Moore, Huss, Vickers,

Glasberg and Alcantra, (2000). In approximately 90% of hearing impaired adults and 75% of

hearing impaired children the degree of impairment worsens from 500 Hz to 4 KHz (Macrae &

Dillon, 1996). Most hearing impaired individuals include a greater loss of hearing sensitivity at

high frequencies than at low frequencies. High frequency sensorineural hearing loss is the most

common configuration and type of hearing loss which results from destruction of inner hair cells

IHCs within cochlea Engstrom (1983), Borg, Canlon and Engstrom, (1995).

Individuals with moderate to severe hearing loss at high frequencies often do not benefit

from amplification of high frequencies or even perform more poorly when high frequencies are

amplified (Villchur, 1973; Moore, 1986; Murray & Byrne, 1986; Hogan & turner, 1998; Moore,

2001; Vickers, Moore & Baer, 2001). It has been suggested that subjects who do not benefit

from amplification of high frequencies have reduced function or complete loss of function of

IHCs and or neurons.

Mc Dermott, Dorkos, Dean and Ching (1999) found that conventional amplifying hearing

aids were of limited use and therefore various attempts had been made to modify them using

filtering, extended frequency response, selective amplification and amplitude compression.

However, the findings on effect of these manipulations can restore missing high frequency

information.

In individuals with steeply sloping loss with high frequency thresholds of about 70 dBHL

or greater the high frequency parts of speech contributes no information. Thus it is essential to

transpose high frequency information to the useful hearing at low frequencies in order to make

high frequency information accessible (Johansson 1961; Wedenberg, 1961; Raymond & Proud

1962; Ling & Druze, 1967; Foust & Gengel, 1973; Velmans & Marcuson, 1983; Rees &

Velmans, 1993; Turner & Hurtig, 1999) using transposition devices and results revealed

significant amount of improvement. Hence there is a need for additional training procedure or an

alternative transposition technique which would result in perceptual benefit for at least some

individuals. Inteo is a new advance in the technology to extend the audibility range into the high

frequencies and it also provides good audibility in regions where the sensitivity is reduced as in

high frequency hearing loss.

Considering all these factors the present study was designed to study the benefit of

frequency transposition hearing aids and to assess the speech identification performances for

individuals with dead regions in two conditions:

1. With Transposition

2. Without Transposition


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Method

Subjects: 10 subjects (15 ears) with moderate to severe sloping high frequency sensorineural

hearing loss with age range of 20 to 75 years were selected for the study. Subjects who were

diagnosed as having Dead Regions were taken for the study.

Stimulus: Standardized high frequency word list and sentence list developed by Mascarenhas &

Yathiraj (2001) was used. The test consists of three lists each with twenty five words and three

sentences lists each with nine sentences.

Recording of Stimulus: These word lists and sentence lists were recorded using a unidirectional

microphone using wave pad software at a sampling rate of 16,000 KHz. Noise reduction and

normalization was done using Audacity software.

Procedure

Step 1: Calibration of audiometer OB922 (dual channel) was done in free field condition.

Step 2: The TEN (HL) test (Moore, 2004) was carried out for diagnosis of dead regions in the

cochlea.

Step By Step Setting Up

1. Feed the left output from the CD player to the left (or A) line. Level input on the audiometer

and the right output from the CD player to the right (or B) input.

2. Select the left (or A) input channel 1 on the audiometer and the right (or B) input for channel 2

on the audiometer.

3. Play track 1, set the audiometer so that both line inputs are played continuously press the

interrupt buttons and adjust vu meter to read 0 dB. Turn off the two inputs (press the interrupt

buttons).

4. Mix the two channels and direct the mixed channel to the desired ear (left or right).

5. Measure the absolute threshold (traditional pure tone audiogram) for each ear at each frequency

using Tracks 2-8 of the CD.

6. Set the desired noise level using the channel 1 control. The level in dB HL /ERB corresponds to

the dial reading on the audiometer.

7. Measure the masked threshold for each ear at each level /frequency using tracks 2-8 of the CD

while playing noise continuously.

8. Repeat steps 4-6 for the other ear if desired.

9. A dead region for a particular frequency is indicated by a masked threshold that is at least 10

dB above the absolute threshold and 10 dB above the TEN (HL) level per ERB.

Step 3: The subjects who fulfilled the standard criteria were included in the study. Their pure

tone thresholds from 250 to 8 KHz for air conduction and from 250 to 4 KHz for bone

conduction of the test ear were fed into the NOAH software.

The subjects were made to sit comfortably

The hearing aid was connected to the Hipro that was in turn connected to a computer with the

programming software

The hearing aid was detected by COMPASS VERSION 4 software after switching the hearing

aid “ON”

Clients data base were created and audiometric data was fed to NOAH software


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Figure I: Fq region to be transposed (Source octave) & where it should be transposed (target octave)

Inteo includes a unique, patent-pending linear frequency transposition algorithm called

the Audibility Extender (AE) which allows people with an unaidable high frequency hearing loss

to hear the missing high frequencies in the lower frequency region. The following description

summarizes the action of the Audibility Extender (AE). First, the inteo AE receives information

of the wearers hearing loss from the dynamic integrator to decide which frequency region will be

transposed. The Audibility Extender picks the frequency within the area „to be transposed‟ or

„source octave‟ region with the highest intensity i.e. peak frequency and locks it for

transposition.

Figure II: Audibility Extender identifies the frequency at 4 KHz in the source octave region to

have the highest peak

In this example, 4000 Hz has the peak intensity

Figure III: Sound with the peak at 4 KHz transposed down by one octave to 2 KHz


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Once identified, the range of frequencies starting from 2500 Hz will be shifted downward

to the target frequency region. In this case, 4000 Hz will be transposed linearly by one octave to

2000 Hz.

Figure IV: Sounds beyond the one octave band width of the 2000 Hz signal will be filtered out

To limit the masking effect from transposed signal, frequencies that are outside the one octave

bandwidth of 2000 Hz will be filtered out. This keeps the frequency ratio between original and

transposed signal.

Figure V: The filtered and transposed signal is amplified and mixed with original signal

The level of transposed signal will be automatically set by the Audibility Extender. A

manual gain adjustment of the transposed signal is also possible. The linearly transposed signal

is mixed with the original signal as the final output. The procedures described above will be

adopted to transpose high frequency sounds to low frequency. In order to see whether sufficient

amplification was provided to the subjects, hearing aid evaluation of performance was carried

out using two programmes 1) INTEO MASTER 2) AUDIBILITY EXTENDER. The subjects‟

task was to repeat back the words and sentences heard. The words and sentences were presented

at 40 dBHL through the speakers of the audiometer. For each subject the level was constant

during unaided and aided conditions. In subjects with asymmetrical hearing loss and hearing loss

in the non test ear, the non test ear was blocked in order to avoid its participation.

Step 4: In the next step the subjects were presented with the standardized list. The list consisted

of 3 lists of 25 high frequency words and 3 lists of 9 sentences in a list which was recorded using

a female voice and was presented through loudspeakers. Different lists were used in each of the


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unaided and aided conditions. All subjects were first evaluated with INTEO MASTER Program

and then with AUDIBILITY EXTENDER program.

Unaided Condition: In quiet, with high frequency words and sentences presented at 40 dBHL

Aided Condition: Two aided conditions were evaluated: In quiet, with high frequency words and

sentences presented at 40 BHL; Without transposition (Inteomaster) and With transposition

(Audibility Extender)

The order of testing was unaided condition, Inteo Master Programme, followed by

Audibility extender programme. Hence a total of 25 words, 9 sentences, in all 3 lists were

presented randomly. The subjects were instructed to repeat the words he/she heard and the

responses were noted down in a response sheet. In speech identification testing each correct

response was given the score of „one‟ and the total number of correct responses was noted down

for each condition for each subject. The speech identification scores for words and sentences

were taken and appropriate statistical analyses were done.

Step 5: Unaided audiogram and the aided audiogram with the Audibility Extender programme

were obtained from 250 Hz to 8 KHz and appropriate statistical analyses were done.

Results

The data obtained from 10 subjects (15 ears) having high frequency sloping hearing

loss with dead regions were analyzed to investigate the benefits of frequency transposition

(Audibility Extender) over Non-transposed (Inteo master) on speech identification scores for

word and sentence using High frequency word and sentence list using Statistical Package for

Social Sciences (Version 10) for windows. The results can be tabulated under the following.

Stage 1: Comparison between Frequencies in Unaided and Aided Conditions: Comparisons

were made for the aided and unaided conditions of frequency transposition for different

frequencies from 250 Hz to 8 KHz.

Table I: The mean and standard deviation (SD) for different frequencies from 250 Hz to 8 KHz

and frequency transposition (Audibility Extender aided condition)

Frequency transposition Frequency (Hz) Mean Standard deviation

Unaided

250 27.9167 16.3009

500 37.0833 20.7209

1K 45.4167 23.6891

2K 69.1667 27.8660

4K 94.1667 15.9307

8K 97.5000 13.5680

Aided (with

Transposition)

250 8.7500 12.4545

500 17.0833 4.5017

1K 23.3333 10.7309

2K 35.0000 19.5402

4K 63.7500 24.7832

8K 82.0833 6.8948


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Frequency (Hz)

8K4K2K1K500250

95%

CI f

or T

hres

hold

s120

100

80

60

40

20

0

Aided

Unaided

Figure VI. The unaided and aided performance with audibility extender

The error bar indicates 95% confidence interval, mean and (+) and (-) standard deviation.

Aided condition variation is less compared to unaided condition. The variation is more in 4 KHz

compared to 500 Hz and 8 KHz. Aided condition is statistically significant compared to unaided

condition.

Comparison on Effect of Unaided and Aided Conditions, Frequencies and the Interaction

between Unaided and Aided Conditions and Frequencies:

Table II: The results of Two-Way Repeated Measure ANOVA

Factor F(df) P

Hearing aid condition F(1,11)=39.33 p<0.001

Frequencies F(5,55)=129.941 p<0.001

Hearing aid conditions *frequencies F(5,55)=1.886 p<0.005

From table II it is evident that there is a significant difference between hearing aid

conditions. There is significant difference between frequencies and there is no significant

interaction between hearing aid conditions and frequencies.

Since there is significant difference between frequencies pair-wise comparisons were

made with Bonferroni‟s multiple comparison test. Based on this test result it is evident that for

frequencies 500 Hz, 1 KHz & 4 kHz, 8 KHz no significant difference was found and all other

pairs of frequencies were significantly different at 5% level of significance. Inorder to clearly

understand the effects of frequency and hearing aid conditions, stepwise analysis was performed

by taking each frequency and each hearing aid condition separately.

Stage 2: Comparison across Frequencies within Unaided Condition:

One-Way Repeated measure ANOVA was performed to see the effect of frequency in

unaided condition. There is significant difference between frequencies in unaided conditions.

F(5,55)=67.913 ,p < 0.001. Since there is significant difference between frequencies in unaided

condition pair-wise comparisons were made with Bonferroni‟s multiple comparison test. Based


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on Bonferroni‟s test, it is evident that for frequencies 250 Hz, 500 Hz and 500 Hz, 1 KHz, 4 KHz

and 8 KHz no significant difference was found and all other pairs of frequencies were

significantly different at 5% level of significance.

Table III. The mean, SD for different frequencies from 250 Hz to 8 KHz in unaided conditions

Frequency (Hz) Mean SD

250 27.9167 16.3009

500 37.0833 20.7209

1K 45.4167 23.6891

2K 69.1667 27.8660

4K 94.1667 15.9307

8K 97.5000 13.5680

Stage 3: Comparison across Frequencies within Aided Condition

Table IV: The mean, SD for different fqs from 250 Hz to 8 KHz in aided condition (with Transposition)

Frequency

(Hz) Mean SD

250 8.7500 11.3074

500 17.0833 4.1404

1k 23.3333 10.5560

2k 35.0000 21.8926

4k 63.7500 26.6056

8k 82.0833 6.7612

One-Way repeated measure ANOVA was performed to see the effect of frequencies in

aided conditions [F (5, 70) = 73.052, p < 0.001]. There is a significant difference between

frequencies in aided condition. Pair-wise comparisons were made with Bonferroni‟s multiple

comparison test. Based on this test it is evident that for frequencies 250 Hz, 500 Hz and 500 Hz,

1 KHz & 4 KHz, 8 kHz no significant difference was found and all other pairs of frequencies

were significantly different at 5% level of significance.

Stage 4: Comparison between Unaided and Aided Conditions within each Frequency

Table V: The mean, SD for aided and unaided condition within each frequency

Frequency (Hz) Mean SD

Unaided 250

Aided 250

30.6667

8.0000

16.5688

11.3074

Unaided 500

Aided 500

40.0000

17.0000

19.9105

4.1404

Unaided 1k

Aided 1k

51.0000

24.0000

24.2899

10.5560

Unaided 2k

Aided 2k

75.3333

41.0000

28.0603

21.8926

Unaided 4k

Aided 4k

95.3846

66.5385

15.8721

25.7702

Unaided 8k

Aided 8k

97.5000

82.0833

13.5680

6.8948


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Comparison of Difference between Aided and Unaided Condition within each Frequency:

Paired t-test was administered to see the difference between aided & unaided conditions within

each frequency.

Table VI. Paired t-test results between aided and unaided conditions within each frequency

Frequency t(df)

250Hz t(14)=4.208*

500Hz t(14)=4.271*

1kHz t(14)=4.876**

2kHz t(14)=6.871**

4kHz t(12)=3.977*

8kHz t(11)=3.890*

* indicates significant at 0.05 level; ** indicates significant at 0.001 level

Stage 5: Comparison of Speech Identification Scores between Unaided, Inteomaster,

Audibility Extender Programmes for Words

Table VII: The mean, SD for unaided, Inteomaster, Audibility extender programs for high fq. words

Conditions Mean SD

Unaided 7.0000 6.7823

Inteomaster 12.2667 4.5272

Audibility extender 15.0000 4.5356

One-way Repeated Measure ANOVA was performed to see the difference between

Unaided, Inteomaster, Audibility extender programmes for words. There is a significant

difference between speech identification scores for word in all three conditions [F (2,28)=34.161,

p<0.001]. Since there is a significant difference, pair-wise comparison was made with

Bonferroni‟s multiple comparison test. Based on this test results it is evident that all are

significantly different from one another at 0.001 level.

Stage 6: Comparison of SIS between Unaided, Inteomaster, Audibility Extender for

Sentences

Table VIII: Shows the mean & SD for unaided, Inteomaster, and Audibility Extender

programmes for high frequency sentences.

Conditions Mean SD

Unaided 11.2667 9.7722

Inteomaster 19.0000 6.0710

Audibility extender 21.4000 5.5136

One-way repeated measure ANOVA was performed to see the difference between

Unaided, Inteomaster, Audibility extender programmes for sentences. There is significant

difference between sentence speech identification scores, F (2, 28) =32.768, p < 0.001. Since


223

there is a significant difference between sentences speech identification scores, pair-wise

comparison were made with Bonferroni‟s multiple comparison test. Based on this test results, it

is evident that all are significantly different at 0.001 level.

WordsSentences

95%

CI f

or S

IS

30

20

10

0

Audibility Extender

Inteomaster

Unaided

Figure VII. Depicts the speech identification scores for Audibility Extender, Inteomaster and

unaided conditions for sentences and words

Error bar depicts the 95% confidence level the mean and (+) and (-) standard deviation,

for audibility extender the variation is less compared to inteomaster and unaided condition for

sentences and also for words.

Discussion

Like in the previous studies evaluating FRED transposition with hearing impaired

individuals (Velmans, 1975; Velmans & Marcuson 1980; Velmans et al., 1982; Velmans et al.,

1988; Rees & Maxvelmans, 1993) the present study has also shown that transposition to be

beneficial. In the present study 10 individuals (15 ears) with moderate to severe high frequency

steeply sloping hearing loss with dead region participated. Dead region was evaluated using a

TEN test. Word and sentence identification task was carried out using high frequency word and

sentence list which was recorded using a female voice. INTEO device were used it has an

integrated signal processing stratergy (ISP). Currently there are two main approaches to signal

processing: Sequential processing and Parallel processing.

In Sequential processing the flow of information is always in one direction. Because of

this sequential nature no two components may be working simultaneously. In Parallel processing

different components occurs at same time. The limitation of both strategies is that the

information from different functional units is not shared among each other. As a result wearer

satisfaction may not be ensured in all situations.

Integrated signal processing (ISP): ISP is newest approach to hearing aid signal

processing where not only the input signal shared among the different functional units but the

results of the processing from each functional unit are also shared amongst each other to result in

a highly complex and integrated network of information flow. All the processes within the

hearing aid function as a unit. This improves the quality of the processed sounds. Because the


224

information is shared among all components the use of more complex algorithms which further

enhance the performance of the hearing aid and wearer satisfaction are possible. Results of the

present study reveals that transposition helps in improving the identification of high frequency

words and sentences and also when unaided and aided performance was compared results show a

statistically significant difference between both conditions.

Unlike the present study McDermott and Dean (2000) carried out study on six adults with

a very steeply sloping high frequency hearing loss. A control group of 5 adults with normal

hearing participated in the study. Normal hearing individuals listened to speech material through

a low pass filter with a cut off frequency of 1200 Hz. The transposition was lowered by the

factor of 0.6. Results revealed that frequency transposition had little effect overall on the

perception of speech.

The result of the above study was different from present study because the study by

McDermott and Dean (2000) was carried out in a simulated condition in normal individuals.

And a relatively simple form of frequency lowering technique was used that is to shift each

frequency component in a sound by a constant factor. For e.g., when the factor equals 0.5 all

frequencies are shifted downwards by one octave. The disadvantage of this method is that overall

pitch of the speech signal is lowered. This may cause female speaker to sound like male speaker.

But in the present study the region with the highest intensity i.e. peak frequency is selected and

locks it for transposition. Once identified the transposition is done linearly by one octave. They

also maintain the frequency ratio between original and transposed signal so that the speech does

not get distorted. The linearly transposed signal is mixed with the original signal at the final

output. Thus helps in better understanding of missing high frequency information.

Conclusion

In the present study 10 subjects (15 ears) with moderate to severe high frequency sloping

hearing loss with dead regions were tested. The speech identification scores were measured using

high frequency word and sentences list for three different conditions unaided, aided

(Inteomaster), aided (Audibility Extender) in quiet at 40 dBHL. The frequencies in unaided and

aided ranging from 250 Hz to 8 KHz were also compared. The data obtained were statistically

analyzed using One-way and two-way repeated ANOVA and paired-t test. Based on the results

the following conclusions are drawn from the study:

1. There was significant difference between unaided and aided (Frequency transposition)

conditions from 250 Hz to 8 KHz.

2. There was significant difference in speech identification scores obtained between

Inteomaster (without transposition) and Audibility extender (with transposition). Thus it

can be inferred that there is statistically significant difference between speech

identification scores in Inteomaster and Audibility Extender conditions and subjective

preferences was for frequency transposition. Majority of individuals who were unable to


225

perceive high frequency information were able to perceive the same after transposition in

the aided condition.

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vocoding of the speech spectrum: Its use by deaf children. Journal of Auditory Research,

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narrow band maskers with fluctuating envelopes. Journal of the Acoustical Scociety of

America, 3, 289-311. Moore, B .C. J., Huss, M., Vickers D. A., Glasberg, B. R., & Alcantra, J. I. (2000). A test for the

diagnosis of dead regions in the cochlea, British Journal of Audiology, 34, 205-224.

Murray, N. & Byrne, D. (1986). Performance of hearing impaired and normal hearing listeners

with various high frequency cutoffs in hearing aids. Australian journal of Audiology, 8,

21-28.

Velmans, M. & Marcuson, M. (1980). A speech like frequency transposing hearing aid for the

sensorineural deaf. children. British Journal of Audiology, 17, 221- 230.

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of speech in quiet for people with and without dead regions at high frequencies. Journal

of the Acoustical Society of America, 110 (2), 1164-1175.

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Raymond, T. H. & Proud, G.O. (1962). Audiofrequency conversion. Archives of Otolaryngology,

76, 436-446.

Ress, R. & Velmans, M. (1993). The effect of frequency transposition on the untrained auditory

discrimination of congenitally deaf children. British Journal of Audiology, 27, 53-60.

Turner, C. W. & Cummings, K. J. (1999). Speech intelligibility for listeners with high frequency

hearing loss. American Academy of Audiology, 8, 47-56.


226

Effect of Cochlear Hearing Loss on Tone Burst Evoked Stacked

Auditory Brainstem Response

Yatin Mahajan & Vanaja C S

Abstract

The auditory brainstem response (ABR) is one of the most useful clinical procedures for

the examination of auditory sensitivity and integrity of auditory system. The conventional ABR is

not sensitive in detecting small acoustic tumors and small intracanalicular tumors. Stacked tone

burst ABR is a new method developed to increase the sensitivity of ABR in detecting small

tumours. It has been reported that cochlear hearing loss affects conventional ABR measures.

Hence, it is possible that cochlear hearing loss also affects stacked ABR. Also a separate

normative data was established for stacked ABR obtained from adding different frequency

specific ABRs. In the present study tone burst ABRs for 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz

were recorded from 22 ears with cochlear hearing loss and thirty five ears with normal hearing.

Stacked ABR was constructed from these tone burst ABRs. The results indicated there is an effect

of number of frequencies used for stacking and amplitude of ABR is largest when ABRs for all

the four frequencies are stacked. The results also revealed that cochlear hearing loss affects the

amplitude of stacked ABR and the reduction in amplitude increases with increase in severity of

hearing loss.

Key words: Frequency Specificity, amplitude, Synchronization.

Introduction

The auditory brainstem response (ABR) is one of the most useful clinical procedures for

the examination of auditory sensitivity and integrity of auditory system. The auditory brainstem

response (ABR) has been well accepted as a procedure to detect retrocochlear pathology (Selters

& Brackmann, 1977; Chandrasekhar, Brackmann & Devgan, 1995; Selesnick & Jackler, 1992;

Welling, Glasscock, Woods & Jackson, 1990; Jerger, Oliver, Chmiel & Rivera, 1986; Starr et al,

1996). However, the sensitivity of ABR in detection of acoustic neuroma, the most common

space occupying lesion on the auditory nerve, depends on its size and location. There are reports

indicating that conventional ABR is not sensitive in detecting small acoustic tumors and small

intracanalicular tumors. Tumors of sizes less than 10 mm and small intracanalicular tumors are

often missed by standard ABR methodology (Telian, Kileny, Niparko, Kemink & Graham, 1989;

Wilson, Hodgson, Gustafson, Hogue & Mills, 1992; Eggermont, Don & Brackmann, 1980;

Schmidt, Satallof, Newmann, Spiegel & Myers, 2001).




227

Studies have reported an increase in incidence of small acoustic tumors over the years

(Stangerup et al., 2004). Tos, Charabi and Thomasen (1999) investigated the distribution of

diagnosed vestibular schwanomas (VS) of various sizes in Denmark from 1976 to 1995 and

reported an increased incidence of intra-canalicular tumors (from 0.4 to 7.9 VS/million/year) and

small tumors (from 13.3 to 29.0 VS/million/year). Similar findings have been reported in other

parts of the world also (Nestor, Karol, Nutik & Smith, 1988; Moffat, Hardy, Irving, Beynon &

Baguley, 1995). Therefore it is essential that audiological tests are developed to identify small

acoustic tumors.

To overcome the disadvantage of standard ABR methodology, Don, Masuda, Nelson and

Brackmann (1997) developed a new ABR measure, called the stacked ABR. The stacked ABR is

a measure which reflects the overall neural activity from a wide frequency region of the cochlea

in response to auditory stimulation. This overall neural activity is a result of synchronized

activity from various regions of the auditory nerve and desynchronization resulting from

compression of a small tumor may be evident in reduction of stacked ABR wave V amplitude

(Don, Kwong, Tanaka, Brackmann & Nelson, 2005; Chandrasekhar, Brackmann & Devgan,

1995). Don, Kwong, Tanaka, Brackmann and Nelson (2005) reported that this method has

demonstrated 95% sensitivity and 88% specificity in detecting small acoustic tumors. Philibert,

Durrant, Ferber-Viart, Duclaux, Veuillet and Collet (2003) used tone burst of different

frequencies instead of derived band technique and waveform obtained were added after aligning

wave V. They reported similar enhancement of wave V amplitude as obtained using derived

band method. They further reported reduced amplitude of the stacked ABR in patients with small

tumors.

There is a dearth of literature on stacked ABR especially tone burst evoked stacked ABR.

Limited research available on stacked ABR indicates that stacked ABR is sensitive in

identification of small acoustic tumors. However, there is a need to standardize this procedure

and also study the factors that can affect the amplitude of stacked ABR. Several investigators

have reported that cochlear hearing loss affects various ABR measures such as absolute

latencies, inter peak latencies, latency intensity function and amplitude measures (Watson, 1996;

Oates & Stapells, 1992; Elberling & Parbo, 1987; Watson, 1999; Coats & Martin, 1977;

Rosenhamer, Lindstrom & Lundborg, 1981; Keith & Greville, 1987). There are very few reports

investigating effect of cochlear hearing loss on amplitude of wave V. The amplitude of the wave

V for click evoked ABR might be smaller in subjects with cochlear hearing loss than in normal

hearing subjects (Xu, Vinck, De Vel & Cauwenberge, 1998; Fowler & Durrant, 1994).

It can be hypothesized that any factor which affects conventional ABR will affect stacked

ABR measure. So it can be hypothesized that cochlear hearing loss has an effect on the

amplitude of stacked ABR. However, there is a dearth of studies in this area. It is essential to

determine the effect of cochlear hearing loss on stacked ABR and consider the effect if any,

while using stacked ABR for neurodiagnostic applications. ABR for five frequencies have been

used to obtain stacked ABR to assess the neural integrity across different frequency regions


228

(Don, Kwong, Tanaka, Brackmann & Nelson, 2005; Philibert et al, 2003). However, using lesser

number of frequencies may reduce the test time. Also in subjects with mild high frequency loss,

ABR for tone bursts of 4000 Hz and/or 2000 Hz might be absent but present for tone bursts of

other frequencies. At such time it will be useful if stacked ABR can be obtained from ABRs of

only two or three frequencies. The amplitude of stacked ABR will depend on the number of

waveforms stacked and the frequency of the stimuli used for recording frequency specific ABR.

Don, Masuda, Nelson and Brackmann (1997) reported a reduction of 33% of amplitude of

derived band stacked ABR when two bands of frequencies were removed in subjects with normal

hearing. So a separate normative data needs to be established for stacked ABR obtained from

adding different frequency specific ABRs. The present study was designed to investigate the

following aims:

1. To investigate the effect of cochlear hearing loss on the tone burst evoked Stacked ABR.

2. To obtain separate normative data for amplitude of stacked ABR obtained from

ABR for 500 Hz, 1000Hz, 2000 Hz & 4000 Hz tone bursts.

ABR for 500 Hz, 1000 Hz & 2000 Hz tone bursts.

ABR for 500 Hz & 1000 Hz tone bursts.

Method

Participants: Participants of the present study were divided into two groups. Group 1 included

thirty five ears of normal hearing individuals aged 15-50 years and hearing sensitivity within 15

dBHL. The group 2 included twenty two ears with cochlear hearing loss of subjects aged 15-50

years with hearing sensitivity within 55 dBHL. Speech identification scores of all 22 subjects

were proportional to pure tone average of 500, 1000 and 2000 Hz and there was no abnormality

indicated on click evoked ABR.

Instrumentation: A calibrated diagnostic audiometer was used for estimating the puretone

thresholds and a calibrated middle ear analyzer to rule out middle ear pathology. Tone burst

evoked stacked ABR was recorded using Intelligent Hearing Systems (Smart EP version 3.86)

evoked potential systems.

Procedure:

Table 1: Test protocol to record Tone burst ABR

Type of stimuli Tone bursts

Transducer Insert ear phones ER-3A

Test frequency 500, 1000, 2000, 4000 Hz

Duration 4 cycles (2-0-2)

Envelope(Gating) Blackmann

No. of stimuli 2000

Repetition rate 11.1/s

Test intensity 80dBnHL

Time window 20ms

Electrode montage Single channel

Polarity Alternate

Sensitivity 50uV

Filter settings 30Hz-3000Hz


229

Pure tone thresholds were obtained at octave frequencies between 250 Hz and 8000 Hz

for air conduction stimuli and between 250 Hz to 4 KHz for bone conduction stimuli using

modified Hughson-Westlake method (Carhart & Jerger, 1959). ABR was recorded for the tone

bursts using the test protocol given in Table 1. The wave V was identified at all test frequencies.

The wave V recorded at all frequencies was time aligned and these aligned waveforms were

added to obtain stacked ABR. The peak-to-trough amplitude of the added waveform was

measured.

Results

The participants of the cochlear hearing loss group were further divided into two groups.

One group consisted of 12 ears with mild cochlear hearing loss (26 dBHL to 40 dBHL) and other

group included 10 ears with moderate cochlear hearing loss (41 dBHL to 55 dBHL). Separate

stacked ABRs were obtained by stacking ABRs for all four frequencies (hereafter called SA),

stacking ABR for 500 Hz, 1000 Hz and 2000 Hz (hereafter called SA3) and stacking ABR for

500 Hz and 1000 Hz (hereafter called SA2). Table 2 shows the mean amplitude and standard

deviation values of stacked ABR for 35 ears with normal hearing and 22 ears with cochlear

hearing loss. The mean amplitude for stacked wave V was largest for SA followed by SA3 and

SA2 in individuals with normal hearing whereas there was not much difference between mean

values for amplitude for SA, SA3 and SA2 for individuals with cochlear hearing loss.

Table 2: Amplitude of stacked ABR for individuals with normal hearing for different stacked

ABRs in micro volts (μV)

Stacked ABR Normal hearing Cochlear hearing loss

N Mean Std. Deviation N Mean Std. Deviation

SA 35 0.54 0.09 19 0.30 0.11

SA3 35 0.53 0.11 21 0.30 0.11

SA2 35 0.50 0.14 22 0.30 0.12

Stacked ABR

SA2SA3SA

95%

CI

.7

.6

.5

.4

.3

.2

.1

Normals

cochlear HL

Figure 1: Error bars showing the upper and lower bounds of amplitude at 95% confidence

interval at different stacked ABRs for two groups


230

Figure 1 shows error bars for the upper and lower bounds of amplitude at 95%

confidence interval at different stacked ABRs for two groups and it can be observed from figure

that there is no overlap between the range of 95% confidence interval for individuals with

cochlear hearing loss and those with normal hearing for all stacked ABRs. There is a large gap

between lower bound of normal hearing and upper bound for cochlear hearing loss group.

Table 3 shows the mean amplitude and standard deviation values of stacked ABR for 12

ears with mild cochlear hearing loss and 10 ears with moderate cochlear hearing loss. The mean

amplitude for stacked wave V is largest for SA than other two stacked ABRs in individuals with

mild cochlear hearing loss and the mean amplitude for stacked wave V was largest for SA2 than

other two stacked ABRs i.e. SA and SA3 in individuals with moderate cochlear hearing loss.

Table 3: Amplitude of stacked ABR for individuals with mild hearing loss and moderate

cochlear hearing loss for different stacked ABRs in micro volts (μV)

Mild cochlear hearing loss Moderate cochlear hearing loss

Stacked ABR N Mean Std. Deviation N Mean Std. Deviation

SA 10 0.36 0.11 9 0.24 0.08

SA3 12 0.34 0.09 9 0.25 0.11

SA2 12 0.34 0.14 10 0.26 0.08

Results of Mann Whitney U test revealed that there is a significant difference (p<0.01) in

mean amplitude of stacked wave V for all stacked ABRs between individuals with normal

hearing and individuals with mild cochlear hearing loss and a significant difference was

observed between amplitude of stacked wave V between individuals with normal hearing and

individuals with moderate cochlear hearing loss for all stacked ABRs. Amplitude of stacked

wave V differed significantly (p<0.05) between the individuals with mild hearing loss and

individuals with moderate hearing loss for only SA.

Stacked ABR

SA2SA3SA

95%

CI

.7

.6

.5

.4

.3

.2

.1

Normals

Mild HL

Moderate HL

Figure 2: Error bars showing the upper and lower bounds of amplitude at 95% confidence

interval at different stacked ABRs for three groups


231

It can be observed from Figure 2 that the range of 95% confidence interval for

individuals with normal hearing loss is extremely different from range for individuals with mild

cochlear hearing loss or moderate cochlear hearing at all frequencies. But the ranges of 95%

confidence interval for mild hearing loss and moderate hearing loss are overlapping for all

stacked ABRs.

Discussion

Amplitude of stacked wave V in individuals with normal hearing ranged from 0.50µV to

0.57µV for SA which is lesser than the range reported by Philibert et al (2003). This can be

attributed to the differences in the methodology used in the two studies. Philibert et al (2003)

tried to approximate the methodology of Don, Masuda, Eggermont and Nelson (1997) and hence

used five frequencies to obtain frequency specific ABR. In the present study standard

audiometric frequencies were used due to time constraints. Also the duration of the stimuli in the

present study was 2-0-2 cycle as compared to 2-1-2 cycle used by Philibert et al (2003).

Results of the present study also showed an increase in stacked wave V amplitude with

the increase in the number of frequencies included for stacking in individuals with normal

hearing. This may be due to the increase in number of neural elements that contribute to the

response (Don, Ponton, Eggermont & Masuda, 1994). So it was observed that SA had more

amplitude as it involves four frequencies which results in more synchronization and higher

amplitude in individuals with normal hearing. Don, Masuda, Nelson and Brackmann (1997) also

reported similar results in which there were a reduction of 33% of amplitude of derived band

evoked stacked ABR when two bands were removed and waveforms were stacked. The

reduction in amplitude of stacked wave V with reduction in number of frequencies used in

stacking could be because of lesser number of averages in the final stacked ABR. It has been

reported in literature that the amplitude of wave V increases with increase in number of averages

(Hall, 1992; Hood, 1998). However, studies also indicate that change in amplitude is not

significant when the number of averages is increased beyond 2000 (Hall, 1992). In the present

study at each frequency 2000 sweeps were averaged. Therefore the effect of number of sweeps

on amplitude of ABR would be minimal. So the effect on amplitude of stacked ABR was due to

cochlear hearing loss.

In individuals with cochlear hearing loss there was a significant reduction in stacked

wave V amplitude for all the stacked ABRs when compared to those individuals with normal

hearing. This may be attributed to the fact that cochlear hearing loss results in abnormal

functioning of different neural elements across the cochlea. It is known that stacked ABR is a

result of total synchronized neural activity from different neural elements (Don, Kwong, Tanaka,

Brackmann & Nelson, 2005). So reduction in input to neural fibers due to cochlear hearing loss

will result in a significant reduction in stacked ABR amplitude.

Though the amplitude values of stacked wave V of different stacked ABRs were not

significantly different in individuals with mild and moderate cochlear hearing loss the amplitude

was reduced in individuals with moderate hearing loss. This may be attributed to the fact that


232

with the increase in hearing loss there will be more damaged regions in the cochlea which

consequently reduces the number of neural fibers stimulated leading to reduced amplitude.

To summarize, the results of the present study indicate that the amplitude of stacked ABR

depends on number of tone bursts evoked ABRs used for stacking. The results also revealed that

cochlear hearing loss affects the amplitude of stacked ABR and the reduction in amplitude

increases with increase in severity of hearing loss.

Conclusions

The results of the present study indicate that amplitude of ABR is largest when ABRs for

all the four frequencies are stacked. There is a significant difference between mean amplitude of

stacked ABR of individuals with normal hearing and individuals with cochlear hearing loss. The

amplitude of stacked ABR for individuals with mild hearing loss as well as moderate hearing

loss is significantly lesser than that of normal individuals. Though not statistically significant the

amplitude of stacked ABR reduces with increase in degree of hearing loss.

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