Single-trial EEG source reconstruction for brain-computer interface.

Brain/physiology; Brain Mapping/methods; Electroencephalography/methods; Evoked Potentials/physiology; Humans; Man-Machine Systems; Pattern Recognition, Automated/methods; User-Computer Interface

Abstract :

[en] A new way to improve the classification rate of an EEG-based brain-computer interface (BCI) could be to reconstruct the brain sources of EEG and to apply BCI methods to these derived sources instead of raw measured electrode potentials. EEG source reconstruction methods are based on electrophysiological information that could improve the discrimination between BCI tasks. In this paper, we present an EEG source reconstruction method for BCI. The results are compared with results from raw electrode potentials to enable direct evaluation of the method. Features are based on frequency power change and Bereitschaft potential. The features are ranked with mutual information before being fed to a proximal support vector machine. The dataset IV of the BCI competition II and data from four subjects serve as test data. Results show that the EEG inverse solution improves the classification rate and can lead to results comparable to the best currently known methods.

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Noirhomme, Quentin ; Université de Liège - ULiège > Centre de recherches du cyclotron

Kitney, Richard I

Macq, Benolt

Language :

English

Title :

Single-trial EEG source reconstruction for brain-computer interface.

Publication date :

2008

Journal title :

IEEE Transactions on Biomedical Engineering

ISSN :

0018-9294

eISSN :

1558-2531

Publisher :

IEEE, New York, United States - New York

Volume :

Issue :

Pages :

1592-601

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 27 October 2010

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2 (1 by ULiège)

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