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

Y. Yang; S. Chevallier; J. Wiart; I. Bloch

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

Y. Yang, S. Chevallier, J. Wiart, I. Bloch

Physical Therapy and Human Movement Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Scopus citations

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.

Original language	English (US)
Title of host publication	ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Publisher	i6doc.com publication
Pages	109-114
Number of pages	6
ISBN (Print)	9782874190490
State	Published - Jan 1 2012
Event	20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012 - Bruges, Belgium Duration: Apr 25 2012 → Apr 27 2012

Publication series

Name	ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Other

Other	20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012
Country	Belgium
City	Bruges
Period	4/25/12 → 4/27/12

ASJC Scopus subject areas

Information Systems
Artificial Intelligence

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Cite this

Yang, Y., Chevallier, S., Wiart, J., & Bloch, I. (2012). Automatic selection of the number of spatial filters for motor-imagery BCI. In ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 109-114). (ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning). i6doc.com publication.

Yang, Y. ; Chevallier, S. ; Wiart, J. ; Bloch, I. / Automatic selection of the number of spatial filters for motor-imagery BCI. ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publication, 2012. pp. 109-114 (ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

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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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Yang, Y, Chevallier, S, Wiart, J & Bloch, I 2012, Automatic selection of the number of spatial filters for motor-imagery BCI. in ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, i6doc.com publication, pp. 109-114, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012, Bruges, Belgium, 4/25/12.

Automatic selection of the number of spatial filters for motor-imagery BCI. / Yang, Y.; Chevallier, S.; Wiart, J.; Bloch, I.

ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publication, 2012. p. 109-114 (ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Yang Y, Chevallier S, Wiart J, Bloch I. Automatic selection of the number of spatial filters for motor-imagery BCI. In ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publication. 2012. p. 109-114. (ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).