HMM and IOHMM Modeling of EEG Rhythms for Asynchronous BCI Systems

We compare the use of two Markovian models, HMMs and IOHMMs, to discriminate between three mental tasks for brain computer interface systems using an asynchronous protocol. We show that IOHMMs outperform HMMs but that, probably due to the lack of any prior information on the state dynamics, no practical advantage in the use of these models over their static counterparts is obtained.


Published in:
European Symposium on Artificial Neural Networks ESANN
Presented at:
European Symposium on Artificial Neural Networks ESANN
Year:
2004
Keywords:
Note:
IDIAP-RR 03-49
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 Record created 2006-03-10, last modified 2018-11-26

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