Robust common spatial filters with a maxmin approach

Motoaki Kawanabe, Carmen Vidaurre, Simon Scholler, Klaus Robert Müller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

Electroencephalographic signals are known to be non-stationary and easily affected by artifacts, therefore their analysis requires methods that can deal with noise. In this work we present two ways of calculating robust common spatial patterns under a maxmin approach. The worst-case objective function is optimized within prefixed sets of the covariance matrices that are defined either very simply as identity matrices or in a data driven way using PCA. We test common spatial filters derived with these two approaches with real world brain-computer interface (BCI) data sets in which we expect substantial "day-to-day" fluctuations (session transfer problem). We compare our results with the classical common spatial filters and show that both can improve the performance of the latter.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages2470-2473
Number of pages4
ISBN (Print)9781424432967
DOIs
Publication statusPublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2009 Sep 22009 Sep 6

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period09/9/209/9/6

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

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  • Cite this

    Kawanabe, M., Vidaurre, C., Scholler, S., & Müller, K. R. (2009). Robust common spatial filters with a maxmin approach. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 2470-2473). [5334786] (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5334786