Document Detail

Electromyography interference pattern decomposition.
MedLine Citation:
PMID:  2059134     Owner:  NLM     Status:  MEDLINE    
Decomposition of an interference pattern enables examination of individual electromyography (EMG) motor units and their firing rates at more than minimal contraction forces. In this decomposition method, significant events with a constant occurrence (near motor unit action potentials) can be enhanced, and unwanted events (distant motor unit action potentials, artifacts) eliminated, by calculating the average accumulated change while sliding a fixed-width window along the digitized EMG interference pattern. Nonparametric statistical methods are then applied to these data to determine which information is significant at the .05 level. The exact duration of significant information is identified without the need for arbitrary thresholds and filters to eliminate unwanted information. Events are then classified into groups of similar events by comparing: (1) correlation coefficients, (2) point-to-point differences, (3) amplitudes, and (4) areas. The classification is further refined by the use of firing-rate information.
R L Joynt; R F Erlandson; S J Wu; C M Wang
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Archives of physical medicine and rehabilitation     Volume:  72     ISSN:  0003-9993     ISO Abbreviation:  Arch Phys Med Rehabil     Publication Date:  1991 Jul 
Date Detail:
Created Date:  1991-08-01     Completed Date:  1991-08-01     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  2985158R     Medline TA:  Arch Phys Med Rehabil     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  567-72     Citation Subset:  AIM; IM    
Department of Physical Medicine and Rehabilitation, Wayne State University, Detroit.
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MeSH Terms
Action Potentials / physiology
Motor Neurons / physiology
Muscle Contraction / physiology*
Signal Processing, Computer-Assisted

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

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