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

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publicationESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Publisheri6doc.com publication
Pages109-114
Number of pages6
ISBN (Print)9782874190490
StatePublished - Jan 1 2012
Event20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012 - Bruges, Belgium
Duration: Apr 25 2012Apr 27 2012

Publication series

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

Other

Other20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012
CountryBelgium
CityBruges
Period4/25/124/27/12

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ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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.