Article (Scientific journals)
Modern electrophysiological methods for brain-computer interfaces.
Grave de Peralta Menendez, Rolando; Noirhomme, Quentin; Cincotti, Febo et al.
2007In Computational Intelligence and Neuroscience, p. 56986
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Keywords :
BCI; brain-computer interface
Abstract :
[en] Modern electrophysiological studies in animals show that the spectrum of neural oscillations encoding relevant information is broader than previously thought and that many diverse areas are engaged for very simple tasks. However, EEG-based brain-computer interfaces (BCI) still employ as control modality relatively slow brain rhythms or features derived from preselected frequencies and scalp locations. Here, we describe the strategy and the algorithms we have developed for the analysis of electrophysiological data and demonstrate their capacity to lead to faster accurate decisions based on linear classifiers. To illustrate this strategy, we analyzed two typical BCI tasks. (1) Mu-rhythm control of a cursor movement by a paraplegic patient. For this data, we show that although the patient received extensive training in mu-rhythm control, valuable information about movement imagination is present on the untrained high-frequency rhythms. This is the first demonstration of the importance of high-frequency rhythms in imagined limb movements. (2) Self-paced finger tapping task in three healthy subjects including the data set used in the BCI-2003 competition. We show that by selecting electrodes and frequency ranges based on their discriminative power, the classification rates can be systematically improved with respect to results published thus far.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Grave de Peralta Menendez, Rolando
Noirhomme, Quentin ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Cincotti, Febo
Mattia, Donatella
Aloise, Fabio
Gonzalez Andino, Sara
Language :
English
Title :
Modern electrophysiological methods for brain-computer interfaces.
Publication date :
2007
Journal title :
Computational Intelligence and Neuroscience
ISSN :
1687-5265
eISSN :
1687-5273
Publisher :
Hindawi Publishing Corporation
Pages :
56986
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 27 October 2010

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