PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

HMM and IOHMM Modeling of EEG Rhythms for Asynchronous BCI Systems
Silvia Chiappa and Samy Bengio
In: European Symposium on Artificial Neural Networks (ESANN), 27-29 April 2004, Bruges, Belgium.

Abstract

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 a priori information on the state dynamics, no practical advantage in the use of these models over their static counterparts is obtained.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Brain Computer Interfaces
ID Code:665
Deposited By:Silvia Chiappa
Deposited On:29 December 2004