TY - GEN
T1 - Optimizing spatio-temporal filters for improving Brain-Computer Interfacing
AU - Dornhege, Guido
AU - Blankertz, Benjamin
AU - Krauledat, Matthias
AU - Losch, Florian
AU - Curio, Gabriel
AU - Müller, Klaus Robert
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - Brain-Computer Interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability of multi-channel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the superiority of the proposed algorithm. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithmcan also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
AB - Brain-Computer Interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability of multi-channel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the superiority of the proposed algorithm. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithmcan also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
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M3 - Conference contribution
AN - SCOPUS:84864032249
SN - 9780262232531
T3 - Advances in Neural Information Processing Systems
SP - 315
EP - 322
BT - Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
T2 - 2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
Y2 - 5 December 2005 through 8 December 2005
ER -