title: EEG sensor selection by sparse spatial filtering in P300 speller brain-computer interface.
abstract: A Brain-Computer Interface (BCI) is a specific type of human-machine interface that enables communication between a subject/patient and a computer by direct control from decoding of brain activity. This paper deals with the P300-speller application that enables to write a text based on the oddball paradigm. To improve the ergonomics and minimize the cost of such a BCI, reducing the number of electrodes is mandatory. We propose a new algorithm to select a relevant subset of electrodes by estimating sparse spatial filters. A l(1)-norm penalization term, as an approximation of the l(0)-norm, is introduced in the xDAWN algorithm, which maximizes the signal to signal-plus-noise ratio. Experimental results on 20 subjects show that the proposed method is efficient to select the most relevant sensors: from 32 down to 10 sensors, the loss in classification accuracy is less than 5%.
authors.affiliation: GIPSAlab, CNRS-UMR 5216, Grenoble Institute of Technology, France. bertrand.rivet@gipsa-lab.grenoble-inp.fr
authors.forename: Bertrand
authors.initials: B
authors.lastname: Rivet
authors.forename: Hubert
authors.initials: H
authors.lastname: Cecotti
authors.forename: Ronald
authors.initials: R
authors.lastname: Phlypo
authors.forename: Olivier
authors.initials: O
authors.lastname: Bertrand
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Maby
authors.forename: Jeremie
authors.initials: J
authors.lastname: Mattout
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D006801:Humans; D010775:Photic Stimulation; D012984:Software; D014584:User-Computer Interface