Abstract

Brain-Computer interface (BCI) is a promising field of research that can change life as we know it, staring from the healthcare, home devices and armed force to video gaming. BCI provides a new communication channel between human and computers using brain signals to perform certain control actions. BCI systems can help physically impaired patients to increase their degree of independence, and give hope to ‘Locked-In Syndrome’ (LIS) Patients and Amyotrophic Lateral Sclerosis ALS to communicate again. The aim of this thesis is to develop a Generic BCI system that uses Blink and Wink as control signals. This system avoids problems like long training periods, the risks of flashing lights and using many electrodes and sophistication of hybrid systems. Blinks and Winks are signals generated by the eye lid muscles and it is considered as an artifact in the brain signals. In this study we propose the use of this artifact signals to recognize human intention. The reason behind choosing blink and wink signals is because its features can be distinguishable from the normal brain activities which allow the system to easily detect it. The Blink and Wink based BCI system uses oddball paradigm technique to facilitate the use for more interactive commands. The system is tested with P300 speller and smart home control panel. For P300 Speller test the system achieved 87.5% accuracy and for the smart home control panel test the system achieved 92.5% accuracy. The test shows that the developed system is generic and efficient as no offline training for calibration was done by any of the subjects while the system achieved better accuracy compared to other BCI systems.

Department

Robotics, Control & Smart Systems Program

Degree Name

MS in Robotics, Control and Smart Systems

Graduation Date

2-1-2016

Submission Date

September 2016

First Advisor

Habib, Maki

Committee Member 1

Gadallah, Yasser

Committee Member 2

Eldawlatly, Seif

Extent

131 P.

Document Type

Master's Thesis

Rights

The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy.

Institutional Review Board (IRB) Approval

Approval has been obtained for this item

Comments

I would like to express my sincere gratitude to my advisor Dr. Maki Habib the director of Master program in Robotics, Control and Smart Systems (RCSS) in Mechanical Engineering Department, School of Sciences and Engineering at The American University in Cairo. Thanks for his continuous support of my Master’s study and research, for his patience, motivation, enthusiasm, and immense knowledge. His guidance helped me in all the time of research and writing of this thesis. I also would like to thank all the students who voluntarily participated in my thesis tests for their time and enthusiasm to try new technology and for all their supportive words and impressions after trying the proposed system they really pushed me forward.

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