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A simple generative model for single-trial EEG classification

: Kohlmorgen, J.; Blankertz, B.


Dorronsoro, J.R.:
ICANN 2002. International Conference on Artificial Neural Networks. Proceedings : Madrid, Spain, August 28 - 30, 2002
Berlin: Springer, 2002 (Lecture Notes in Computer Science 2415)
ISBN: 3-540-44074-7
ISSN: 0302-9743
International Conference on Artificial Neural Networks (ICANN) <12, 2002, Madrid>
Conference Paper
Fraunhofer FIRST ()

In this paper we present a simple and straightforward approach to the problem of single-trial classification of event-related potentials (ERP) in EEG. We exploit the well-known fact that event-related drifts in EEG potentials can well be observed if averaged over a sufficiently large number of trials. We propose to use the average signal and its variance as a generative model for each event class and use Bayes decision rule for the classification of new, unlabeled data. The method is successfully applied to a data set from the NIPS*2001 Brain-Computer Interface post-workshop competition.