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Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces
Abstract : Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific channel selection method based on a criterion called F score to realize the parameterization of both time segment and channel positions. The F score is a novel simplified measure derived from Fisher's discrimi-nant analysis for evaluating the discriminative power of a group of features. The experimental results on a standard dataset (BCI competition III dataset IVa) show that our method can efficiently reduce the number of channels (from 118 channels to 9 in average) without a decrease in mean classification accuracy. Compared to two state-of-the-art methods in channel selection, our method leads to comparable or even better classification results with less selected channels.
https://hal.archives-ouvertes.fr/hal-01351620
Contributor : Sylvain Chevallier Connect in order to contact the contributor
Submitted on : Friday, August 5, 2016 - 10:30:15 AM
Last modification on : Wednesday, November 3, 2021 - 6:04:16 AM
Long-term archiving on: : Sunday, November 6, 2016 - 10:20:14 AM
Contributor : Sylvain Chevallier Connect in order to contact the contributor
Submitted on : Friday, August 5, 2016 - 10:30:15 AM
Last modification on : Wednesday, November 3, 2021 - 6:04:16 AM
Long-term archiving on: : Sunday, November 6, 2016 - 10:20:14 AM
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