Classification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution.

@article{Demirer2009ClassificationOI,
  title={Classification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution.},
  author={Rustu Murat Demirer and Mehmet Sirac Ozerdem and Coşkun Bayrak},
  journal={Journal of neuroscience methods},
  year={2009},
  volume={178 1},
  pages={214-8}
}
The study presented in this paper shows that electrocorticographic (ECoG) signals can be classified for making use of a human brain-computer interface (BCI) field. The results show that certain invariant phase transition features can be reliably used to classify two types of imagined movements accurately. Those are the left small-finger and tongue movements. Our approach consists of two main parts: channel selection based on Tsallis entropy in Hilbert domain and the nonlinear classification of… CONTINUE READING
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