Ensemble of SVMs for improving brain computer interface p300 speller performances

Authors:
A. Rakotomamonjy;V. Guigue;G. Mallet;V. Alvarado
Affiliations:
P.S.I CNRS FRE 2645 INSA de Rouen, Saint Etienne du Rouvray, France;P.S.I CNRS FRE 2645 INSA de Rouen, Saint Etienne du Rouvray, France;P.S.I CNRS FRE 2645 INSA de Rouen, Saint Etienne du Rouvray, France;P.S.I CNRS FRE 2645 INSA de Rouen, Saint Etienne du Rouvray, France
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Year:
2005

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Abstract

This paper addresses the problem of signal responses variability within a single subject in P300 speller Brain-Computer Interfaces. We propose here a method to cope with these variabilities by considering a single learner for each acquisition session. Each learner consists of a channel selection procedure and a classifier. Our algorithm has been benchmarked with the data and the results of the BCI 2003 competition dataset and we clearly show that our approach yields to state-of-the art results.