Motor imagery ECoG signals classification using wavelet transform features

Abstract

The input signals of brain computer interfaces may be either electroencephalogram (EEG) recorded from scalp or electrocorticogram (ECoG) recorded with subdural electrodes. It is very important that the classifiers have the ability for discriminating signals which are recorded in different sessions to make brain computer interfaces practical in use. This… (More)

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Cite this paper

@article{Aydemir2010MotorIE, title={Motor imagery ECoG signals classification using wavelet transform features}, author={Onder Aydemir and Temel Kayikçioglu}, journal={2010 IEEE 18th Signal Processing and Communications Applications Conference}, year={2010}, pages={296-299} }