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Combined optimization of spatial and temporal filters for improving brain-computer interfacing

: Dornhege, G.; Blankertz, B.; Krauledat, M.; Losch, F.; Curio, G.; Müller, K.-R.


IEEE Transactions on Biomedical Engineering BME 53 (2006), No.11, pp.2274-2281
ISSN: 0018-9294
ISSN: 1558-2531
Journal Article
Fraunhofer FIRST ()

Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output de ice 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 rates of multichannel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.