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