Discrimination of Four Classes in Brain-Computer Interface Based on Motor Imagery

Mahgoub, Tasneem Mahmoud Salih; Supervisor - Omer E. H. Hamid

dc.contributor.author	Mahgoub, Tasneem Mahmoud Salih
dc.contributor.author	Supervisor - Omer E. H. Hamid
dc.date.accessioned	2014-06-01T11:08:58Z
dc.date.available	2014-06-01T11:08:58Z
dc.date.issued	2010-10-01
dc.identifier.citation	Mahgoub,Tasneem Mahmoud Salih .Discrimination of Four Classes in Brain-Computer Interface Based on Motor Imagery/Tasneem Mahmoud Salih Mahgoub;Omer E. H. Hamid .-Khartoum:Sudan University of Science and Technology,College of Engineering,2010.-62p. : ill. ; 28cm.-M.Sc.	en_US
dc.identifier.uri	http://repository.sustech.edu/handle/123456789/5358
dc.description	Thesis	en_US
dc.description.abstract	Brain–computer interface provides a voluntarily, non-manual control for artificial limb or device by translating brain activity patterns into control commands. The research 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 proposed techniques were evaluated by Cohen's kappa coefficient and gave average accuracy around (97+2%) in session one and (31+4%) in session two in classifying four different motor imageries (MI) from EEG measurements for nine subjects under investigating.	en_US
dc.description.sponsorship	Sudan University of Science and Technology	en_US
dc.language.iso	en	en_US
dc.publisher	Sudan University of Science and Technology	en_US
dc.subject	Brain - Computer Interface
dc.subject	Biomedical Engineering	en_US
dc.subject	HUMAN BRAIN	en_US
dc.title	Discrimination of Four Classes in Brain-Computer Interface Based on Motor Imagery	en_US
dc.title.alternative	تمييز أربع إشارات حيوية في نظام الاتصال بين الدماغ البشري والحاسوب اعتماداً على إشارة الحركة التخيلية	en_US
dc.type	Thesis	en_US