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Multi-objective particle swarm optimization for channel selection in brain-computer interfaces

Hasan, BAS and Gan, JQ (2009) Multi-objective particle swarm optimization for channel selection in brain-computer interfaces. In: Proceedings of the UK Workshop on Computational Intelligence (UKCI 2009), ? - ?, Nottingham.

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Abstract

This paper presents a novel application of a multi-objective particle swarm optimization (MOPSO) method to solve the problem of effective channel selection for Brain-Computer Interface (BCI) systems. The proposed method is tested on 6 subjects and compared to another search based method, Sequential Floating Forward Search (SFFS). The results demonstrate the effectiveness of MOPSO in selecting a fewer number of channels with insignificant sacrifice in accuracy, which is very important to build robust online BCI systems.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 01 Jul 2013 13:05
Last Modified: 17 Aug 2017 18:07
URI: http://repository.essex.ac.uk/id/eprint/4148

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