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Conference papers
Subject-specific channel selection for classification of morot imagery electroencephalographic data
Abstract : Brain-computer interfaces (BCIs) are systems that record brain signals
and then classify them to generate computer commands. Keeping
a minimal number of channels (electrodes) is essential for developing
portable BCIs. Unlike existing methods choosing channels
without optimization of time segment for classification, this work
proposes a novel subject-specific channel selection method based on
a criterion derived from Fisher’s discriminant analysis to realize the
parametrization of both time segment and channel positions. The
experimental results show that the method can efficiently reduce the
number of channels (from 118 channels to no more than 11), and
shorten the training time, without a significant decrease of classification
accuracy on a standard dataset.
https://hal.telecom-paris.fr/hal-02286514
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 3:51:05 PM
Last modification on : Friday, July 31, 2020 - 11:28:07 AM
Contributor : Telecomparis Hal <>
Submitted on : Friday, September 13, 2019 - 3:51:05 PM
Last modification on : Friday, July 31, 2020 - 11:28:07 AM
