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Automatic selection of the number of spatial filters for motor-imagery BCI

Abstract : Common spatial pattern (CSP) is widely used for constructing spatial filters to extract features for motor-imagery-based BCI. One main parameter in CSP-based classification is the number of spatial filters used. An automatic method relying on Rayleigh quotient is presented to estimate its optimal value for each subject. Based on an existing dataset, we validate the contribution of the proposed method through a study of the effect of this parameter on the classification performance. The evaluation on testing data shows that the estimated subject-specific optimal values yield better performances than the recommended value in the literature.
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Submitted on : Monday, October 1, 2012 - 2:11:46 PM
Last modification on : Thursday, October 7, 2021 - 10:48:10 AM
Long-term archiving on: : Wednesday, January 2, 2013 - 6:35:11 AM


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  • HAL Id : hal-00737242, version 1



Yuan Yang, Sylvain Chevallier, Joe Wiart, Isabelle Bloch. Automatic selection of the number of spatial filters for motor-imagery BCI. The proceeding of 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), Apr 2012, Bruges, Belgium. pp.109-114. ⟨hal-00737242⟩



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