@article{DornhegeBlankertzKrauledatetal.2006,
  author    = {Dornhege, Guido and Blankertz, Benjamin and Krauledat, Matthias and Losch, Florian and Curio, Gabriel and M{\"u}ller, Klaus-Robert},
  title     = {Combined optimization of spatial and temporal filters for improving brain-computer interfacing},
  series = {IEEE transactions on bio-medical electronics},
  volume    = {53},
  journal   = {IEEE transactions on bio-medical electronics},
  number    = {11},
  publisher = {IEEE},
  address   = {New York},
  issn      = {0018-9294},
  doi       = {10.1109/TBME.2006.883649},
  pages     = {2274 -- 2281},
  year      = {2006},
  abstract  = {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.},
  language  = {en}
}