Principal component based covariate shift adaption to reduce non-stationarity in a MEG-based brain-computer interface

@article{Spler2012PrincipalCB,
  title={Principal component based covariate shift adaption to reduce non-stationarity in a MEG-based brain-computer interface},
  author={Martin Sp{\"u}ler and Wolfgang Rosenstiel and Martin Bogdan},
  journal={EURASIP J. Adv. Sig. Proc.},
  year={2012},
  volume={2012},
  pages={129}
}
One of the biggest problems in today’s BCI research is the non-stationarity of the recorded signals. This non-stationarity can cause the BCI performance to deteriorate over time or drop significantly when transfering data from one session to another. To reduce the effect of non-stationaries, we propose a new method for covariate shift adaption that is based on Principal Component Analysis to extract non-stationaries and alleviate them. We show the proposed method to significantly increase BCI… CONTINUE READING
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