Evolving spatial and frequency selection filters for Brain-Computer Interfaces
作者： Ricardo Aler , Ines M. Galvan , Jose M. Valls
关键词: Frequency domain 、 Frequency dependence 、 CMA-ES 、 Brain–computer interface 、 Support vector machine 、 Artificial intelligence 、 Classifier (UML) 、 Computer science 、 Pattern recognition 、 Evolution strategy 、 Data mining
摘要: Machine Learning techniques are routinely applied to Brain Computer Interfaces in order learn a classifier for particular user. However, research has shown that classification perform better if the EEG signal is previously preprocessed provide high quality attributes classifier. Spatial and frequency-selection filters can be this purpose. In paper, we propose automatically optimize these by means of Covariance Matrix Adaptation Evolution Strategy (CMA-ES). The technique been tested on data from BCI-III competition, because both raw manually filtered datasets were supplied, allowing compare them. Results show CMA-ES able obtain higher accuracies than tuned filters.
sci-hub.se 参考文章(15)
Judea Pearl, Heuristics : intelligent search strategies for computer problem solving ,(1984)
Guido Dornhege, José del R Millán, Thilo Hinterberger, Dennis J McFarland, Klaus-Robert (eds.) Müller, Toward brain-computer interfacing : MIT Press. ,(2007)
Andreas Ostermeier, Andreas Gawelczyk, Nikolaus Hansen, A derandomized approach to self-adaptation of evolution strategies Evolutionary Computation. ,vol. 2, pp. 369- 380 ,(1994) , 10.1162/EVCO.1994.2.4.369
Ferran Galán, Francesc Oliva, Joan Guàrdia, Using mental tasks transitions detection to improve spontaneous mental activity classification. Medical & Biological Engineering & Computing. ,vol. 45, pp. 603- 609 ,(2007) , 10.1007/S11517-007-0197-7
Gert Pfurtscheller, Christa Neuper, Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man Neuroscience Letters. ,vol. 174, pp. 93- 96 ,(1994) , 10.1016/0304-3940(94)90127-9
Eleanor A Curran, Maria J Stokes, Learning to control brain activity: A review of the production and control of EEG components for driving brain–computer interface (BCI) systems Brain and Cognition. ,vol. 51, pp. 326- 336 ,(2003) , 10.1016/S0278-2626(03)00036-8
Nikolaus Hansen, Andreas Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies Evolutionary Computation. ,vol. 9, pp. 159- 195 ,(2001) , 10.1162/106365601750190398
S. Lemm, B. Blankertz, G. Curio, K.-R. Muller, Spatio-Spectral Filters for Improving the Classification of Single Trial EEG IEEE Transactions on Biomedical Engineering. ,vol. 52, pp. 1541- 1548 ,(2005) , 10.1109/TBME.2005.851521
Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten, The WEKA data mining software ACM SIGKDD Explorations Newsletter. ,vol. 11, pp. 10- 18 ,(2009) , 10.1145/1656274.1656278
Keinosuke Fukunaga, Introduction to Statistical Pattern Recognition ,(1972)