IT10088074(1)

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Brain Computer Application Interface IT10088074

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The Brain Computer

InterfaceApplication Framework

H.G .Udayanga

(IT10088074)BSc. (Hons) in Information Technology

Department of Information Technology

Sri Lanka Institute of Information Technology

Sri Lanka

August 2013

Declaration

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I declare that this is my own work and this report does not incorporate withoutacknowledgment any material previously submitted for a Degree or Diploma in anyother University or institute of higher learning and to the best of my knowledge andbelief it does not contain any material previously published overwritten by another

person except where the acknowledgment is made in the text. Also, I hereby grant to SriLanka Institute of Information Technology the nonexclusive right to reproduce anddistribute my dissertation, in whole or in part in print, electronic or other medium. I retainthe right to use this content in whole or part in future works (such as articles or books).

Signature:

Date:The above candidate has carried out research for the B.Sc Dissertation under mysupervision.

Signature of the supervisor:Date:

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AbstractBrain computer interfaces are emerging research area. Brain computer interfaces hasstepped from scientific fictions to consumer devices .Apart from research grade BCIdevices, low cost consumer devices has come to the market. In this project we aregoing to build a Application framework for Neurosky Mind wave, a low cost consumer

grade BCI device. Furthermore we are going to investigate the capability of device tocontrol a third party applications such as a game or Assistive application. We are goingto find the suitable applications for this kind of device and propose and implementsoftware wise enhancement for this type of Applications.

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Acknowledgment

Upon this page we humbly put down our thoughts of deepest gratitude for all those whoguided us in our endeavors to create the Tourism Portal.

Though it seems impossible to name all those who lent us a helping hand along ourway, we would like to mention a few names in representation of all our mentors. We firstconvey our utmost gratitude to Mr.Jayantha Lal Amararachchi (Student Coordinator andLecturer, Sri Lanka Institute of Information Technology) Drs. Rohana Thilakumara(Supervisor, Lecturer, Sri Lanka Institute of Information Technology), and Mr. DarshikaKoggalahewa(Co-supervisor, Assistant Lecturer, Sri Lanka Institute of InformationTechnology), for providing us with proper guidance for the Comprehensive Design

Analysis Project and guiding us along the correct path.

We wish to thank all our fellow students who helped us in numerous ways to make thisproject a success. Finally with a wave of gratitude for all those Well-wishers andmentors whose names we failed to mention, we bring this Statement ofacknowledgment to conclusion.

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Contents

INTRODUCTION & RESEARCH ............................................................................................................. 6

Background Context .............................................................................................................................. 7

Research Problem ................................................................................................................................. 8

Research Gap......................................................................................................................................... 8

Research Problem Questions .............................................................................................................. 9

Literature Survey .................................................................................................................................... 9

Methodology.............................................................................................................................................. 11

System Architecture............................................................................................................................. 11

System Overview ................................................................................................................................. 12

BCI Enhanced Key Board ................................................................................................................... 12

BCI Enhanced LUDO Game............................................................................................................... 14Methodology.......................................................................................................................................... 17

Overview of the implementation methodology............................................................................. 18

RESULTS DISCUSSION ........................................................................................................................ 18

Technologies used ............................................................................................................................... 19

References ................................................................................................................................................ 20

List of Abbreviations

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BCI { (Brain Computer Interface) - is a direct communication pathway between thebrain and an external device.

Neurosky { is a manufacturer of BCI technologies for consumer product applications.

Mindwave {BCI - consumer grade BCI manufactured by Neurosky

EEG {(Electroencephalography ) - is the recording ofelectrical activity along the scalp

ThinkGear { -is a library for communication between Neurosky BCI and aComputer

C#{ An object-oriented programming language

INTRODUCTION & RESEARCH
http://en.wikipedia.org/wiki/Electricalhttp://en.wikipedia.org/wiki/Scalphttp://en.wikipedia.org/wiki/Scalphttp://en.wikipedia.org/wiki/Scalphttp://en.wikipedia.org/wiki/Electrical

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Background Context

Brain-Computer Interface (BCI) technology is a potentially powerful communication andcontrol option in the interaction between Human and Computer systems. A BrainComputer Interface (BCI) is a direct communication pathway between the brain and an

external device. This technology enables signals that are generated in the brain tocontrol an external activity such as control of a keyboard of a computer or control of awheelchair. Over the past few years, variety of applications have been developed thatare exclusively for use with a EEG headset by companies like Neurosky and Emotiv. Inthis proposal we are proposing novel a brain computer application interface that can befacilitated in developing brain controlled applications. By proposing this frame work wetry break down barrier between brain computer interface researchers and softwaredevelopers community. Our proposed framework will facilitate to professionaldevelopers as well as independent enthusiast to dive in to the depth of brain controlledapplication world without bothering about brain wave analyzing, feature extraction andclassification. Furthermore they wouldn't want to brother about devices without

considering devices they would be able to develop their creative gaming ideas. Theobjective of the proposed project is to bring expert knowledge of Neurophysicists towardthe programmers and motivate them to use brain waves as a novel way of controllingcomputers.

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Research Problem

Brain computer interfaces are immerging research area in these days. Manymanufactures have been able to develop consumer grade BCI such as neurosky and

Emotive. There are two main problems arising in developing brain computer

Applications . They are the capability of the devices and required knowledge of

developing brain computer applications.

Most o f consumer level brain computer interfaces which are available in the market

define some parameters using their proprietary algorithms which are kept in secret.

They have marketed their device by saying anyone can build BCI application using

these parameter values. In this project we have use neurosky mind wave a consumer

grade BCI.It has three parameters .They are attention level ,meditation level and blinkstrength .He have research how these parameters are effective in developing Brain

computer applications.

Furthermore we have to investigate what types of applications are suitable for these

types of devices .Most of these devices are marketed as gaming devices. So we have

to find what types of games can be played using these devices.

Research GapIn this project Neurosky mind wave BCI is used. Mind wave has only two sensors. One

is used to measure the EEG activities of our eye and other one is a reference sensors.

It can measure EEG of motor functions. Therefore we forced to defend their defined

parameters

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typical medical laboratory has more or less the same apparatus, disregarding theobvious difference in computer power and digital memory involved in the laboratory.

The EEG recording is obtained by placing electrodes on the scalp with a conductive gel.Most systems use caps or nets into which electrodes are embedded; this is particularly

common when high-density arrays of electrodes are needed. Each electrode isconnected to the input of a differential amplifier (usually one amplifier per pair ofelectrodes). A common system reference electrode is connected to the other input ofeach differential amplifier. The voltage amplification between the active electrode andthe reference is typically 1,000-100,000 times, reaching 60-100 dB of voltage gain. MostEEG systems these days, however, are digital, and the amplified signal is digitized viaan analog-to-digital converter, after being passed through an anti-aliasing filter.

In what research has been done so far, the field information technology & BCI technologyhas develop a wealth of computer technology to support the various aspect of BCItechnology, software applications and Hardware applications. Primarily there are twocategories of BCI systemsinvasive and noninvasive. Invasive systems interact with thebrain directly via electrodes / sensors that are implanted into the brain or its surface. Whilenoninvasive systems interact with the brain indirectly via electrodes / sensors placed on thesurface of the head that detect brain signal emissions (e.g. Electro-Encephalography(EEG), functional Magnetic Resonance Imaging (fMRI), and Magnetic Sensor Systems).

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Methodology

System Architecture

EEG values are captured from Neurosky Mind wave device using device driver and

record them. For that purpose We use Think gear API .Then calculate the attention

,meditation and blink strength values.

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System Overview

Here We have developed two main Application.1) BCI Enhanced Key Board for disabled person2)BCI Enhanced LUDO Game

BCI Enhanced Key Board

Interface of Blink Key Board

This application has been design for disabled users to communicate with the worldithout any communication barriers. The Neurosky device detect the strength of eyeblink. These eye blink is used to control button of the Blink Key Board. First user has toselect the relevant row by blinking user eye when its highlighted. (Wen the Key Board i s

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open button row of it are automatically highlighted from bottom to top) After that thebutton of the selected row highlighted from the left right Blinking eyes user has to selectthe correct button when it is highlighted. After typing all the word of the text SAY ITbutton should be selected then what you have type is pronounced.

BCI Enhanced LUDO game

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Interface of LUDO game

we have developed a Ludo game. The value of the Die of this game is generated

according to the Attention level of the user. If the user is having a higher attention level,

the Die will get higher values. If the attention level of the user is low, the Die will get

lower values.

The Attention level values of the user is given to the application by the BCI device that

is worn by the user. Then Running Average of those values are automatically generated

and those Running Average values decide the value that the Die should get .

Research Findings

Mainly Neurosky Mind wave give us three parameters

1)Attention Level2)Meditation level3)Blink Strength

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These parameters are defined by their proprietary algorithms which are not published.There for we had to check above parameters and usability for consumer level softwareapplicationsWe mainly did three tests using randomly chosen students of our institution.

1)Measure both attention and meditation levels of students while they were reading aparagraph of a book.2) Measure both attention and meditation levels of students while they were listion to amusic3) Measure both attention and meditation levels of students while they were playing acar race game

Attention level -Student A

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120

Attention Level Values

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Attention level -Student B

Given above are some values that we had taken during our Experiments. We can see clearlythat these data are rapidly varying e were able to see same kind of situation in Meditation dataalso. We can use these types of signal for controlling an application. Therefore we calculatedrunning average of collected data

Student A running Average

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60

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Attention Level Values

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10

20

30Running Average of Attention Level Values

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Student B Running Average values

We can clearly observe, even in running average values there is some amount ofvariation .So this type of signals are not suitable for controlling software application. So

we have to select blink strength as our controlling parameter.

Methodology

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Running average of Attention Level Values

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Overview of the implementation methodology

As for the development methodology we use the agile scrum method. Whereas thewhole system is broken break in modules a and individually modules are developed.

Then individual modules are integrated and build the system .Then test. If there need toadd enhancements or correct error build the relevant module and integrate until aefficient and effective system comes out.

RESULTS DISCUSSIONWe initially developed a key board for disable persons and a ludo game using Think gear

Neurosky device can not go beyond that due to the limitation the device. But We have add

enhancements for our applications for user convenience. For example ,The calculator take

considerable amount of time and effort to operate it. We hope to add some methods to reduce

these parameters. We hope to add some word suggestion methods for that.

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Technologies used

1. Neurosky mindwave BCI Device

2. Microsoft Visual Studio 2010

3. Net Framework 3.5

4. C# programming Language

5. Microsoft Excel 2007

Conclusion

In this project we have used a neurosky mind wave device which has only single

sensor. To control advanced application such as 3d games capabilities of the used BCI

devices should be in a high standard level with the fully functional options. Also there

should be many sensors which are capable of capturing brain signal within vast areas of

the brain.

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2010. [Online]. Available:

http://strokengine.ca/intervention/admin/patient/Motor%20Imagery-

Family%20InformationDec2010.pdf.

3. "P300 (neuroscience)," 2012. [Online]. Available:

http://en.wikipedia.org/wiki/P300_(neuroscience). [Accessed 2013].

4. K. Nakayama and M. Mackeben, "Steady State Visual Evoked Potentials In the Alert

Primate," 1982. [Online]. Available:

http://visionlab.harvard.edu/members/ken/Ken%20papers%20for%20web%20page/027

VisionRes82.pdf.

5. "Event-related Potential: An overview," 2011. [Online]. Available:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016705/. [Accessed 2013].

6. "Electroencephalogram (EEG)," WebMD, LLC., 2010. [Online]. Available:

http://www.webmd.com/epilepsy/electroencephalogram-eeg-21508.

7. "What Is A Framework?," 2003. [Online]. Available:

http://www.codeproject.com/Articles/5381/What-Is-A-Framework.

8. "Neurosky MindWave Mobile," Neurosky, 2012. [Online]. Available:

http://neurosky.com/Products/MindWaveMobile.aspx.

9. Microsoft, "Microsoft Visual Studio," Microsoft, 2013. [Online]. Available:

http://www.microsoft.com/visualstudio/eng/products/visual-studio-ultimate-2012.

10. S. Du and M. Vuskovic, "Temporal vs. Spectral Approach to Feature Extraction,"

[Online]. Available:

http://medusa.sdsu.edu/Robotics/Neuromuscular/Our_Publications/FE_Sijiang_press.pd

f.

11. J. B. Ochoa, "EEG Signal Classification for Brain," 2002.

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