Clustering of EEG Occipital Signals using K-means

Víctor Asanza, Kerly Ochoa, Christian Sacarelo, Carlos Salazar, Francis Loayza, Carmen Vacaand Enrique Peláez

Escuela Superior Politécnica del Litoral, ESPOL

Facultad de Ingeniería en Electricidad y Computación

Centro de Tecnología de información

INTRODUCTION:

Kadoya, K., Lu, P., Nguyen, K., Lee-Kubli, C., Kumamaru, H., Yao, L., ... & Takashima, Y. (2016). Spinal cord reconstitution with homologousneural grafts enables robust corticospinal regeneration. Nature medicine.

Astrand, E., Wardak, C., & Ben Hamed, S. (2014). Selective visual attention to drive cognitive brain–machine interfaces: from concepts to

neurofeedback and rehabilitation applications. Frontiers in systems neuroscience, 8, 144.

Different recording methods used to control BMIs

INTRODUCTION:

Obien, M. E. J., Deligkaris, K., Bullmann, T., Bakkum, D. J., & Frey, U. (2015). Revealing neuronal function through microelectrode array

recordings.Frontiers in neuroscience, 8, 423.

Typical electrophysiological methods.

- Macroscopic electroencephalography (EEG).

- Mesoscopic electrocorticography (ECoG).

- Implantable electrodes

Range: uV – 10mVINTRODUCTION:

Jost, W. H., Hefter, H., Reissig, A., Kollewe, K., & Wissel, J. (2014). Efficacy and safety of botulinum toxin type A (Dysport) for the treatment

of post-stroke arm spasticity: Results of the German–Austrian open-label post-marketing surveillance prospective study. Journal of the

neurological sciences, 337(1), 86-90.

Five typical arm spasticity patterns.

INTRODUCTION:

Emotiv EEG electrode locations

www.emotiv.com

INTRODUCTION:

EEG Signal Pre-ProcessingEEG Signal Acquisition

EEG Signal Processing: Feature Selection & K-means Algorithm

METHODOLOGY:

METHODOLOGY:

Visual stimuli generated by a display with LEDs used to acquire the occipital EEG signals.

VOLUNTEERS

Number of healthyvolunteers:

5

Repeat an experiment : 10 times

EMOTIV EPOC

Sampling Rate: 128 samples por second

Channels: 14

Resolution: 14 bits

VISUAL STIMULATION

Frequency: 5, 6, 7, 8, 9, 24, 26, 27, 28, 29 Hz

Duration Time: 19,5 seconds

Distribution of the 2 occipital electrodes Emotiv equipment.

- 2500 Samples.- EEG Electrodes: Left Occipital

(LO) and Right Occipital (RO).

METHODOLOGY:

DC artifacts present in the occipital EEG signals 5Hz visual stimulus.

2500 x 20 10 Frequencies LO10 Frequencies RO

2500 Samples

METHODOLOGY:

2500 x 20 10 Frequencies LO10 Frequencies RO

2500 Samples

2500 x 20 10 Frequencies LO10 Frequencies RO

2500 Samples

2500 x 20 10 Frequencies LO10 Frequencies RO

2500 Samples

2500 x 20 10 Frequencies LO10 Frequencies RO

2500 Samples

f=: 5, 6, 7, 8, 9, 24, 26, 27, 28, 29 Hz

An analysis to the FFT frequency of the EEG signal.

METHODOLOGY:

a) Histogram of the EEG signal without pre-processing to occipital area with5Hz visual stimulus.

b) Comparison between the distribution of the EEG acquired data vs datafrom a normal distribution.

- H0: EEG were not normal distributed with zero mean and variance value of 1.

- H1: EEG were normal distributed with zero mean and variance value of 1.

METHODOLOGY:

Butterworth filter 3er Orden (2-40)Hz

METHODOLOGY:

RESULTS :

EEG signal whithout DC artifacts in the 2 electrodes of the occipital area.

Frequency analysis filtered with the FFT of the EEG signals.

RESULTS :

a) Histogram of the EEG signal with pre-processing to occipital area with 5Hz visual stimulus.

b) Comparison between the distribution of the EEG acquired data vs data from a normal distribution.

- H0: EEG were not normal distributed with zero mean and variance value of 1.

- H1: EEG were normal distributed with zero mean and variance value of 1.

RESULTS :

RESULTS :

FEATURES

Variance (Time and Frequency): Var(t,f)

Covariance (Time and Frequency): Cov(t,f)

Correlation (Time and Frequency): Corr(t,f)

Index Maximun Frequency: WhichMax(f)

Minimum, Maximum, Median, Arithmetic average:

Time and Frequency

Features Slection

100 x 30 30 ([7 F. Time + 8 F. Frequency]

x 2 electrodes)

100(5 Volunteers

x 10 Frequencyx 2 Electrodes)

Sum Squared Erros (SS) vs the number of k clusters

RESULTS :

HIT RESULTS USING K-MEANS TO DIFFERENT GROUPS OF FEATURES.

EEG signals in the frequency range 5-9 Hz (cluster 1) and in the range of 24 to 29 Hz (cluster 2).

RESULTS :

CONCLUSIONS :- Normal distribution test on EEG.

- Better cluster is obtaining by measuring the values of the index of maximum frequency.- One in the frequency range of 5 through 9 Hz (cluster 1) and another in the range of 24 to 29 Hz (cluster 2).

To learn more about this work:

- IEEExplore: http://ieeexplore.ieee.org/abstract/document/7750874/

- Mail vasanza: vasanza@espol.edu.ec

- Project: Semantic Interpretation of Brain Signals