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An automated method for relevant frequency bands identification based on genetic algorithms and dedicated to the Motor Imagery BCI protocol

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3 Author(s)
Parini, S. ; Politec. di Milano Univ., Milan ; Maggi, L. ; Andreoni, G.

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.

Published in:

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Date of Conference:

22-26 Aug. 2007