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Time-frequency Selection in Two Bipolar Channels for Improving the Classification of Motor Imagery EEG
Abstract : Time and frequency information is essential to feature extraction in a motor imagery BCI, in particular for systems based on a few channels. In this paper, we propose a novel time-frequency selection method based on a criterion called Time-frequency Discrimination Factor (TFDF) to extract discriminative event-related desynchronization (ERD) features for BCI data classification. Compared to existing methods, the proposed approach generates better classification performances (mean kappa coefficient = 0.62) on experimental data from the BCI competition IV dataset IIb, with only two bipolar channels.
Cited literature [18 references]
https://hal.archives-ouvertes.fr/hal-00737280
Contributor : Yuan Yang Connect in order to contact the contributor
Submitted on : Monday, October 1, 2012 - 2:35:28 PM
Last modification on : Thursday, October 7, 2021 - 10:48:10 AM
Long-term archiving on: : Wednesday, January 2, 2013 - 6:45:10 AM
Contributor : Yuan Yang Connect in order to contact the contributor
Submitted on : Monday, October 1, 2012 - 2:35:28 PM
Last modification on : Thursday, October 7, 2021 - 10:48:10 AM
Long-term archiving on: : Wednesday, January 2, 2013 - 6:45:10 AM
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EMBC12_0320_FI.pdf
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