Performance of channel selection used for Multi-class EEG signal classification of motor imagery

In this paper, a study of a non-invasive brain-machine interfaces for the classification of 4 imaginary are presented. Performance comparisons using time-frequency analysis between the Linear Discriminant Analysis motor activities (left hand, right hand, foot, tongue) with the BCI competition III da...

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Main Authors: Kheira, Djelloul (Author), Beladgham, M. (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2019-09-01.
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LEADER 02020 am a22003013u 4500
001 ijeecs17844_12889
042 |a dc 
100 1 0 |a Kheira, Djelloul  |e author 
100 1 0 |e contributor 
700 1 0 |a Beladgham, M.  |e author 
245 0 0 |a Performance of channel selection used for Multi-class EEG signal classification of motor imagery 
260 |b Institute of Advanced Engineering and Science,   |c 2019-09-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/17844 
520 |a In this paper, a study of a non-invasive brain-machine interfaces for the classification of 4 imaginary are presented. Performance comparisons using time-frequency analysis between the Linear Discriminant Analysis motor activities (left hand, right hand, foot, tongue) with the BCI competition III dataset IIIa is (LDA), the Support Vector Machine (SVM) and the K-Nearest Neighbors (KNN) algorithms have been carried. The number and position of electrodes for each subject were investigated to provide an improvement for the classification accuracy of the algorithm. Results show that the electrode positions varied from subject to subject; moreover , using one subset of the channels enhanced the classification performances compared to literature data. an average accuracy of 86.06% was observed among all 3 subjects. 
540 |a Copyright (c) 2019 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 15, No 3: September 2019; 1305-1312 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v15.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/17844/12889 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/17844/12889  |z Get fulltext