NDLI: Utilization of Genetic Algorithm for Optimal EEG Channel Selection in Brain-Computer Interface Application

Content Provider	IEEE Xplore Digital Library
Author	Hasan, I.H. Ramli, A.R. Ahmad, S.A.
Copyright Year	2014
Description	Author affiliation: Inst. of Adv. Technol., Univ. Putra Malaysia, Serdang, Malaysia (Hasan, I.H.) \|\| Fac. of Eng., Univ. Putra Malaysia, Serdang, Malaysia (Ramli, A.R.; Ahmad, S.A.)
Abstract	Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields since it is an important element in assistive technology. The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from 32 to 64 electrodes' recordings and translate them to a movement using various computing algorithm which can be used in wheelchair navigation, or control robot movements. However, it will be time consuming and an exhausting experience if the single command translation from large number of electrodes is used. The aim of this project is to develop an algorithm that can choose optimal four electrodes for signal recording, and convert one thought into multiple commands with the chosen electrodes. Using sample datasets, the EEG signal is analyzed to determine the most suitable scalp area for P300 detection, while optimization with genetic algorithm (GA) is developed to select best four channels. After 30 GA runs, the optimal four sets of electrodes are chosen based on their coefficient of determination or $r^{2}$ values, where higher values contributes to higher repetition rates. Using signals from the chosen four electrodes, a success rate of 75-80% is received.
Starting Page	97
Ending Page	102
File Size	358433
Page Count	6
File Format	PDF
e-ISBN	9781479979103
DOI	10.1109/ICAIET.2014.25
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-03
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrodes Signal processing algorithms Brain-Computer Interface; Genetic Algorithm; EEG; P300 Signal processing Feature extraction Electroencephalography Optimization Genetic algorithms
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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