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| Research article summary (published 29 Apr 2008): |
Single-trial EEG source reconstruction for brain-computer interface.
Full Abstract
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.
Author information
Author/s: Noirhomme, Quentin (Q); Kitney, Richard I (RI); Macq, Benolt (B);
Affiliation: Communications and Remote Sensing Laboratory, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium. noirhomme(-atsign-)tele.ucl.ac.be
Journal and publication information
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal: IEEE transactions on bio-medical engineering (IEEE Trans Biomed Eng), published in United States. (Language: eng)
Reference: 2008-May; vol 55 (issue 5) : pp 1592-601
Dates: Created 2008/04/28; Completed 2008/06/27;
PMID: 18440905, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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