Research Repository

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

Al Moubayed, N and Hasan, BAS and Gan, JQ and Petrovski, A and McCall, J (2012) Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. In: IEE Congress on Evolutionary Computation 2012, 2012-06-10 - 2012-06-15, Brisbane, Australia.

Continuous Presentation for Multi-objective Channel Selection in Brain-Computer Interfaces.pdf

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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 (D2MOPSO) 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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Notes:
Uncontrolled Keywords: D2MOPSO; EEG cap space; EEG Channel; SFFS; brain-computer interface; channel physical location; channel selection problem; classification enhancement; classification error rate; continuous presentation; electroencephalograph cap; mental task; multi-objective channel selection; multi-objective particle swarm optimization method; particle movement; projected 2D space; right-vs-left motor imagery BCI; search space; sequential floating forward search
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Jan 2015 16:38
Last Modified: 23 Sep 2022 18:46

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