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primary topic: Enhancing EEG Signals in Brain Computer Interface Using Intrinsic Time-Scale Decomposition

Enhancing EEG Signals in Brain Computer Interface Using Intrinsic Time-Scale Decomposition
type: AcademicArticle
type: Article
abstract: A brain-computer interface (BCI) provides a link between the human brain and a computer. The EEG signal is nonlinear and non-stationary. Feature extraction is one of the most important steps in any BCI system; as such, enhancement to the existing methods has been incorporated in this work. For this, we propose a four-class movement imaginations of the right hand, left hand, both hands, and both feet, and develop feature extraction methods utilizing an intelligent method based on intrinsic time-scale decomposition (ITD) and Artificial neural networks (ANN). Based on the processed electroencephalography (EEG) data recorded from nine subjects, ITD accurately classified and discriminated the four classes of motor imagery; the average accuracy achieved is 92.20. © Published under licence by IOP Publishing Ltd.
date: 2018
volume: 1123
issue: 1
is part of: Journal of Physics: Conference Series
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ConferenceItemEPrint
is part of: repository

Institute of Physics Publishing
type: Organization

Journal of Physics: Conference Series
type: Collection
issn: 17426588

E. Ali Hamid
type: Person
given name: E.
family name: Ali Hamid

I. Khalil Adam
type: Person
given name: I.
family name: Khalil Adam

E. Abdalsalam Mohamed
type: Person
given name: E.
family name: Abdalsalam Mohamed

M. Muzammel
type: Person
given name: M.
family name: Muzammel

M. Zuki Yusoff
type: Person
given name: M.
family name: Zuki Yusoff

F. Al-Shargie
type: Person
given name: F.
family name: Al-Shargie

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primary topic: Enhancing EEG Signals in Brain Computer Interface Using Intrinsic Time-Scale Decomposition