Robust classification of motor imagery EEG signals using statistical time-domain features.

@article{Khorshidtalab2013RobustCO,
  title={Robust classification of motor imagery EEG signals using statistical time-domain features.},
  author={Aida Khorshidtalab and Momoh Jimoh El Salami and Maryam Hamedi},
  journal={Physiological measurement},
  year={2013},
  volume={34 11},
  pages={1563-79}
}
The tradeoff between computational complexity and speed, in addition to growing demands for real-time BMI (brain-machine interface) systems, expose the necessity of applying methods with least possible complexity. Willison amplitude (WAMP) and slope sign change (SSC) are two promising time-domain features only if the right threshold value is defined for them. To overcome the drawback of going through trial and error for the determination of a suitable threshold value, modified WAMP and modified… CONTINUE READING
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