Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG.

Yuan Yang; Sylvain Chevallier; Joe Wiart; Isabelle Bloch

doi:10.1109/EMBC.2012.6346532

Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG.

Yuan Yang^*, Sylvain Chevallier, Joe Wiart, Isabelle Bloch

^*Corresponding author for this work

Physical Therapy and Human Movement Sciences

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

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.

Original language	English (US)
Pages (from-to)	2744-2747
Number of pages	4
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
DOIs	https://doi.org/10.1109/EMBC.2012.6346532
State	Published - Dec 1 2012

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

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Yang, Y., Chevallier, S., Wiart, J., & Bloch, I. (2012). Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2744-2747. https://doi.org/10.1109/EMBC.2012.6346532

Yang, Yuan ; Chevallier, Sylvain ; Wiart, Joe ; Bloch, Isabelle. / Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG. In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2012 ; pp. 2744-2747.

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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.",

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Yang, Y, Chevallier, S, Wiart, J & Bloch, I 2012, 'Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, pp. 2744-2747. https://doi.org/10.1109/EMBC.2012.6346532

Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG. / Yang, Yuan; Chevallier, Sylvain; Wiart, Joe; Bloch, Isabelle.

In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 01.12.2012, p. 2744-2747.

Research output: Contribution to journal › Article › peer-review

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Yang Y, Chevallier S, Wiart J, Bloch I. Time-frequency selection in two bipolar channels for improving the classification of motor imagery EEG. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2012 Dec 1;2744-2747. https://doi.org/10.1109/EMBC.2012.6346532