An automated method for relevant frequency bands identification based on genetic algorithms and dedicated to the...

This paper presents an automated method for relevant frequency bands identification to be used in a left/right hand motor imagery based Brain Computer Interface system. The adopted optimization method aimed at maximizing the ratio between the mutual information and the error rate obtained using a Regularized Linear Discriminant Analysis (RLDA) based classifier and band-specific amplitude modulated envelopes as features. The search problem was handled by a genetic algorithm starting from an initial population determined on the basis of a-priori mu and beta relevant frequency bands identified by means of a standard power spectral density analysis between the idle and the left/right imagery data subset.