STUDY ON CLASSIFICATION OF IMAGINARY HAND MOVEMENTS BASED ON WAVELET PACKET ENTROPY
Ren Ya-li · Acta Biophysica Sinica · 2008
Based on wavelet packet entropy derived from EEG,a method of classification of imagining hand movements was proposed.The EEG signals have been recorded during the imagination of left or right hand movement.The wavelet packet entropy of EEG and its dynamic changing properties with respect to time and windows length have been analyzed.The event-related EEG patterns during imagining left and right hand movement were identified by using linear discriminant algorithm.The results show that the method is effective and the correct rate of classification is up to 92.14 %.Since the computation of wavelet packet entropy is simple,the result is stable,and the identification rate is high,the new method might provide a new way for the classification of mental tasks.