DocumentCode :
2514018
Title :
MUAP Classification Based on Wavelet Packet and Fuzzy Clustering Technique
Author :
Ren, Xiaomei ; Huang, Hua ; Deng, Lihua
Author_Institution :
Coll. of Electr. Eng. & Inf. Technol., Sichuan Univ., Chengdu, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
4
Abstract :
The present study compares several methods with regard to feature extraction and classification of motor unit action potentials (MUAPs) for electromyography (EMG) signal decomposition. The technique was applied to single-channel, short-period real myoelectric signals from normal subjects and artificially generated EMG recordings. All the real EMG recordings were made from the biceps brachii of healthy subjects during voluntary contraction at different force. A model, based on the phenomenon of EMG signal, is used to test the proposed technique on synthetic signals with known features. In contrast to previously developed methods based on EMG signal decomposition performance, our technique has two important distinctive characteristics. Firstly, we applied the local discriminant optimal wavelet packet for the feature extraction of MUAPs. Secondly, we optimized the MUAP classification result using the fuzzy C-means clustering technique to improve the EMG decomposition accuracy. Therefore, the method is substantially automatic and has been evaluated with synthetic and experimentally recorded myoelectric signals.
Keywords :
biomechanics; biomedical measurement; electromyography; feature extraction; fuzzy set theory; medical signal processing; neurophysiology; pattern clustering; signal classification; wavelet transforms; MUAP classification; artificially generated EMG recording; biceps brachii voluntary contraction; electromyography signal decomposition; feature extraction; fuzzy C-means clustering technique; local discriminant optimal wavelet packet technique; motor unit action potential; Electrodes; Electromyography; Feature extraction; Needles; Pattern analysis; Shape control; Shape measurement; Signal resolution; Wavelet coefficients; Wavelet packets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
Type :
conf
DOI :
10.1109/ICBBE.2009.5163091
Filename :
5163091
Link To Document :
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