Brain Computer Interface Enhancement by Independent Component Analysis

Authors: P. Bobrov, A. A. Frolov, Dušan Húsek
Publication year: 2013
Publication type: Konferenční příspěvek (mezinárodní konf.)
Periodical: Proceedings of the Third International Conference on Intelligent Human Computer Interaction IHCI 2011
Projects: Decompositions of matrices with binary and ordinal data: theory, algorithms, and complexity
Methods of Artificial Inteligence in GIS
Bibliographic citation: BOBROV, P., FROLOV, A. A., HÚSEK, Dušan. Brain Computer Interface Enhancement by Independent Component Analysis. In: KUDĚLKA, M., POKORNÝ, J., SNÁŠEL, V., ABRAHAM, A., eds. Proceedings of the Third International Conference on Intelligent Human Computer Interaction IHCI 2011. Heidelberg: Springer, 2013, S. 51-60. Advances in Intelligent Systems and Computing, 179. ISBN 978-3-642-31602-9. ISSN 2194-5357
Dostupné z: doi:10.1007/978-3-642-31603-6_5
DOI: 10.1007/978-3-642-31603-6_5
ID: 368470

Abstract

Brain-Computer Interface is aimed as a direct communication pathway between human or animal brain and an external device. A reliable, accurate and fast identification of a being’s intention based on EEG signal scanning is crucial part of the system. To improve the classification accuracy we propose to use Independent Component Analysis for mi-rhythm identification in data corresponding to motor imagery task performance during Brain-Computer Interface training and operation. We show that independent components corresponding to the mi-rhythm allow for higher classification accuracy comparing to raw EEG recordings usage.