Document Detail


MUAP extraction and classification based on wavelet transform and ICA for EMG decomposition.
MedLine Citation:
PMID:  16937179     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We have developed an effective technique for extracting and classifying motor unit action potentials (MUAPs) for electromyography (EMG) signal decomposition. This technique is based on single-channel and short perioda9s real recordings from normal subjects and artificially generated recordings. This EMG signal decomposition technique has several distinctive characteristics compared with the former decomposition methods: (1) it bandpass filters the EMG signal through wavelet filter and utilizes threshold estimation calculated in wavelet transform for noise reduction in EMG signals to detect MUAPs before amplitude single threshold filtering; (2) it removes the power interference component from EMG recordings by combining independent component analysis (ICA) and wavelet filtering method together; (3) the similarity measure for MUAP clustering is based on the variance of the error normalized with the sum of RMS values for segments; (4) it finally uses ICA method to subtract all accurately classified MUAP spikes from original EMG signals. The technique of our EMG signal decomposition is fast and robust, which has been evaluated through synthetic EMG signals and real EMG signals.
Authors:
Xiaomei Ren; Xiao Hu; Zhizhong Wang; Zhiguo Yan
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2006-04-20
Journal Detail:
Title:  Medical & biological engineering & computing     Volume:  44     ISSN:  0140-0118     ISO Abbreviation:  Med Biol Eng Comput     Publication Date:  2006 May 
Date Detail:
Created Date:  2006-08-28     Completed Date:  2007-08-10     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7704869     Medline TA:  Med Biol Eng Comput     Country:  United States    
Other Details:
Languages:  eng     Pagination:  371-82     Citation Subset:  IM    
Affiliation:
Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, Peoplea's Republic of China. xmren@sjtu.edu.cn
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MeSH Terms
Descriptor/Qualifier:
Action Potentials / physiology*
Algorithms
Electromyography*
Humans
Motor Neurons / physiology*
Signal Processing, Computer-Assisted*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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