Identification of Surface EMG Signals Using Wavelet Packet Entropy
نویسندگان
چکیده
This paper introduces a novel and simple algorithm to extract the feature from Surface EMG signals recorded from the skin surface over forearm muscles. Surface EMG signal is decomposed into 16 frequency bands (FB) by wavelet packet transform (WPT), and then wavelet packet entropy (WPE) of every surface EMG signal is calculated by its relative wavelet energy in every FB. WPE is regarded as the feature to distinguish forearm supination (FS) surface EMG signals from forearm pronation (FP) surface EMG signals. The results show that WPE is an effective method to extract the feature from surface EMG signal. Key-Words: -Surface EMG signal; Wavelet packet transform; Wavelet packet entropy; Bayes decision
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