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EEG-based brain-computer interface using subject-specific spatial filters

  • Bio-inspired Systems
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Engineering Applications of Bio-Inspired Artificial Neural Networks (IWANN 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1607))

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Abstract

Sensorimotor EEG rhythms are affected by motor imagery and can, therefore, be used as input signals for an EEG-based brain-computer interface (BCI). Satisfactory classification rates of imagery-related EEG patterns can be activated when multiple EEG recordings and the method of common spatial patterns is used for parameter estimation. Data from 3 BCI experiments with and without feedback are reported.

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Author information

Authors and Affiliations

  1. Department of Medical Informatics, Institute of Biomedical Engng. and Ludwig Boltzmann Institute of Medical Informatics and Neuroinformatics, University of Technology, Graz, Inffeldgasse 16a, 8010, Graz, Austria

    G. Pfurtscheller, C. Guger & H. Ramoser

Authors
  1. G. Pfurtscheller
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  2. C. Guger
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  3. H. Ramoser
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Editor information

José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Pfurtscheller, G., Guger, C., Ramoser, H. (1999). EEG-based brain-computer interface using subject-specific spatial filters. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100491

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  • DOI: https://doi.org/10.1007/BFb0100491

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66068-2

  • Online ISBN: 978-3-540-48772-2

  • eBook Packages: Springer Book Archive

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