NDLI: Discrimination of four classes in Brain Computer Interface based on motor imagery

Content Provider	IEEE Xplore Digital Library
Author	Salih, T.M. Hamid, O.
Copyright Year	2013
Description	Author affiliation: Dept. of Med. Equip. Technol., Salman Bin Abdulaziz Univ., Alkharj, Saudi Arabia (Hamid, O.) \|\| Dept. of Biomed. Eng., Expatriates Univ., Khartoum, Sudan (Salih, T.M.)
Abstract	This study investigated the classification of multiclass motor imagery for electroencephalogram (EEG)-based Brain-Computer Interface (BCI) using independent component analysis (ICA), principle component analysis (PCA) and support vector machine (SVM) techniques. The dataset used is available on BCI competition IV that contains EEG signals for 9 subjects who performed left hand, right hand, foot and tongue motor imageries (MI). The ICA technique appears well suited for performing source separation in domains where the number of independent signal sources is equal to the number of electrodes or sensors, which is not applicable in the case of EEG sources, since we have no idea about the effective number of statistically independent brain signals related to the EEG recorded from the scalp, also we proved that right hand can activate the same areas of left hand in the brain, while foot can activate the same areas of hands and tongue. Thus we did not have high expectations for separating the same signal sources in all sessions and this justify the overall accuracy of 33±2% that we got when using the combination of ICA and SVM techniques.
Starting Page	418
Ending Page	422
File Size	698534
Page Count	5
File Format	PDF
e-ISBN	9781467362320
DOI	10.1109/ICCEEE.2013.6633974
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-26
Publisher Place	Sudan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Motor Imagery Accuracy Tongue Brain Computer Interface Principle component analysis Feature extraction Independent component Analysis Electroencephalography Classification algorithms Support vector machine Principal component analysis Foot
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
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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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