Document Detail


Electromyogram amplitude estimation with adaptive smoothing window length.
MedLine Citation:
PMID:  10356878     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Typical electromyogram (EMG) amplitude estimators use a fixed window length for smoothing the amplitude estimate. When the EMG amplitude is dynamic, previous research suggests that varying the smoothing length as a function of time may improve amplitude estimation. This paper develops optimal time-varying selection of the smoothing window length using a stochastic model of the EMG signal. Optimal selection is a function of the EMG amplitude and its derivatives. Simulation studies, in which EMG amplitude was changed randomly, found that the "best" adaptive filter performed as well as the "best" fixed-length filter. Experimental studies found the advantages of the adaptive processor to be situation dependent. Subjects used real-time EMG amplitude estimates to track a randomly-moving target. Perhaps due to task difficulty, no differences in adaptive versus fixed-length processors were observed when the target speed was fast. When the target speed was slow, the experimental results were consistent with the simulation predictions. When the target moved between two constant levels, the adaptive processor responded rapidly to the target level transitions and had low variance while the target dwelled on a level.
Authors:
E A Clancy
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Publication Detail:
Type:  Clinical Trial; Journal Article    
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  46     ISSN:  0018-9294     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  1999 Jun 
Date Detail:
Created Date:  1999-06-17     Completed Date:  1999-06-17     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  717-29     Citation Subset:  IM    
Affiliation:
Liberty Mutual Research Center for Safety and Health, Hopkinton, MA 01748, USA. ted.clancy@alum.wpi.edu
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MeSH Terms
Descriptor/Qualifier:
Adolescent
Adult
Aged
Algorithms*
Analysis of Variance
Artifacts
Bias (Epidemiology)
Electromyography / methods*
Female
Humans
Isotonic Contraction / physiology*
Linear Models
Male
Middle Aged
Models, Statistical*
Reproducibility of Results
Signal Processing, Computer-Assisted*
Stochastic Processes*
Time Factors

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


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