Document Detail


Methods to reduce the variability of EMG power spectrum estimates.
MedLine Citation:
PMID:  9785248     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Three methods that can significantly reduce the variability of the EMG power density spectrum (PDS) variable by eliminating artifactual components are described. Two methods, one that allows the subtraction of power line noise in the time domain and one which allows the subtraction of system noise in the frequency domain from the EMG, were shown to be effective in helping to accurately estimate the median frequency (MF) of the PDS, and especially during low level contractions (0-25% maximal voluntary contraction, MVC) when the signal-to-noise ratio is unfavorable. The techniques eliminate the artifactual effects of system and power line noises from the EMG recordings throughout the force range (0-100% MVC) while preserving the native EMG power at all frequencies. It was also shown that if a technique to train subjects to produce their true MVC is employed, the absolute force/torque produced could be as much as 30% higher than in untrained MVC. The effect of true MVC production was also shown to be significant when interpretation of PDS variables are correlated to the processes which produce contraction.
Authors:
R V Baratta; M Solomonow; B H Zhou; M Zhu
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology     Volume:  8     ISSN:  1050-6411     ISO Abbreviation:  J Electromyogr Kinesiol     Publication Date:  1998 Oct 
Date Detail:
Created Date:  1998-12-17     Completed Date:  1998-12-17     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9109125     Medline TA:  J Electromyogr Kinesiol     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  279-85     Citation Subset:  IM    
Affiliation:
Louisiana State University Medical Center, Department of Orthopaedic Surgery, New Orleans 70112, USA. rbarat@lsumc.edu
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Artifacts
Electromyography / methods*
Humans
Isometric Contraction / physiology
Muscle Contraction / physiology
Muscle, Skeletal / physiology
Signal Processing, Computer-Assisted*
Stress, Mechanical
Torque

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


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