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

Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus Robert Müller

Research output: Contribution to journalArticlepeer-review

312 Citations (Scopus)


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 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.

Original languageEnglish
Pages (from-to)2274-2281
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Issue number11
Publication statusPublished - 2006 Nov


  • Brain-computer interface
  • Common spatial patterns
  • EEG
  • Event-related desynchronization
  • Single-trial-analysis

ASJC Scopus subject areas

  • Biomedical Engineering


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