Using a Multiple Classifier System for Improving the Performance of Asynchronous Brain Interface Systems

TitleUsing a Multiple Classifier System for Improving the Performance of Asynchronous Brain Interface Systems
Publication TypeConference Paper
Year of Publication2006
AuthorsFatourechi, M., G. E. Birch, and R. K. Ward
Conference NameAcoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
PaginationV -V
Date Publishedmay.
Keywordsasynchronous brain interface systems, electroencephalography, multiple classifier system, multiple EEG channels
Abstract

To improve the performance of asynchronous brain interface (ABI) systems, a new classifier design is proposed. The spatial information of multiple EEG channels data is first used to create independent classifiers for different channels. A subset of these classifiers is then selected by a genetic algorithm to form a multiple classifier system (MCS) to decide whether a trial is an intended control or a no control signal. The analysis of the data from 4 subjects shows the effectiveness of the proposed method in improving the performance of an ABI system compared to the results obtained using only the best performing channel

URLhttp://dx.doi.org/10.1109/ICASSP.2006.1661423
DOI10.1109/ICASSP.2006.1661423

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