• IEEE Trans Biomed Eng · Nov 2006

    Comparative Study

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

    • Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, and Klaus-Robert Müller.
    • Fraunhofer FIRST.IDA, Kekuléstr. 7, 12 489 Berlin, Germany. guido.dornhege@first.fraunhofer.de
    • IEEE Trans Biomed Eng. 2006 Nov 1; 53 (11): 2274-81.

    AbstractBrain-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 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.

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