Classification of motor imagery EEG signals based on energy entropy

Feature extraction and classification of EEG is core issues on brain computer interface.The energy entropy of different motor imagery EEG signals is used to extract features.Finally,classification of Motor Imagery EEG is performed by a method based on the statistical theory.The results show that classification accuracy exceed 90%。