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Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces

Al Moubayed, N; Awwad Shiekh Hasan, B; Gan, JQ; Petrovski, A; McCall, J

Authors

B Awwad Shiekh Hasan

JQ Gan

A Petrovski

J McCall



Abstract

A novel presentation for channel selection problem in Brain-Computer Interfaces (BCI) is introduced here. Continuous presentation in a projected two-dimensional space of the Electroencephalograph (EEG) cap is proposed. A multi-objective particle swarm optimization method (D 2 MOPSO) is employed where particles move in the EEG cap space to locate the optimum set of solutions that minimize the number of selected channels and the classification error rate. This representation focuses on the local relationships among EEG channels as the physical location of the channels is explicitly represented in the search space avoiding picking up channels that are known to be uncorrelated with the mental task. In addition continuous presentation is a more natural way for problem solving in PSO framework. The method is validated on 10 subjects performing right-vs-left motor imagery BCI. The results are compared to these obtained using Sequential Floating Forward Search (SFFS) and shows significant enhancement in classification accuracy but most importantly in the distribution of the selected channels.

Citation

Al Moubayed, N., Awwad Shiekh Hasan, B., Gan, J., Petrovski, A., & McCall, J. (2012). Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. . https://doi.org/10.1109/cec.2012.6252991

Conference Name 2012 IEEE Congress on Evolutionary Computation
Conference Location Brisbane, Australia
Start Date Jun 10, 2012
End Date Jun 15, 2012
Online Publication Date Aug 2, 2012
Publication Date 2012
Deposit Date Jan 26, 2016
Publisher Institute of Electrical and Electronics Engineers
Pages 1-7
Series ISSN 1941-0026
ISBN 978-1-4673-1510-4
DOI https://doi.org/10.1109/cec.2012.6252991
Public URL https://durham-repository.worktribe.com/output/1152508