Motor imagery based Brain Computer Interface with subject adapted time-frequency tiling

@article{Ince2006MotorIB,
  title={Motor imagery based Brain Computer Interface with subject adapted time-frequency tiling},
  author={Nuri Firat Ince and Ahmed H. Tewfik and Sami Arica},
  journal={2006 14th European Signal Processing Conference},
  year={2006},
  pages={1-5}
}
We introduce a new technique for the classification of motor imagery electroencephalogram (EEG) recordings in a Brain Computer Interface (BCI) task. The technique is based on an adaptive time-frequency analysis of EEG signals computed using Local Discriminant Bases (LDB) derived from Local Cosine Packets (LCP). Unlike prior work on adaptive time-frequency analysis of EEG signals, this paper uses arbitrary non-dyadic time segments and adaptively selects the size of the frequency bands used for… CONTINUE READING
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