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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© 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
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