A direct optimization approach to the P300 speller

Authors:
Roberto Santana;Santiago Muelas;Antonio LaTorre;Jose M. Peña
Affiliations:
Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain;Universidad Politécnica de Madrid, Madrid, Spain
Venue:
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Year:
2011

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Abstract

The P300 component of the brain event-related-potential is one of the most used signals in brain computer interfaces (BCIs). One of the required steps for the application of the P300 paradigm is the identification of this component in the presence of stimuli. In this paper we propose a direct optimization approach to the P300 classification problem. A general formulation of the problem is introduced. Different classes of optimization algorithms are applied to solve the problem and the concepts of k-best and k-worst ensembles of solutions are introduced as a way to improve the accuracy of single solutions. The introduced approaches are able to achieve a classification rate over 80% on test data.