Literature DB >> 12872325

Decomposition-based quantitative electromyography: methods and initial normative data in five muscles.

Timothy J Doherty1, Daniel W Stashuk.   

Abstract

Quantitative electromyographic (EMG) techniques provide clinically useful information to aid in the diagnosis and follow the course or response to treatment of diseases affecting the motor system. The purpose of this study was to describe a decomposition-based quantitative electromyography method (DQEMG) designed to obtain clinically applicable information relating to motor unit potential (MUP) size and configuration, and motor unit (MU) firing characteristics. Additionally, preliminary normative data were obtained from the deltoid, biceps brachii, first dorsal interosseous, vastus medialis, and tibialis anterior muscles of 13 control subjects. DQEMG was capable of efficiently and accurately extracting MUP data from complex interference patterns during mild to moderate contractions. MUP amplitude, surface-detected MUP (S-MUP) amplitude, MUP duration, number of phases, and MU firing frequencies varied significantly across muscles. The mean parameter values for the individual muscles studied were similar to previous reports based on other quantitative methods. The main advantages of this method are the speed of data acquisition and processing, the ability to obtain MUPs from MUs with low and higher recruitment thresholds, and the ability to obtain both S-MUP or macro-MUP data as well as MU firing rate information.

Mesh:

Year:  2003        PMID: 12872325     DOI: 10.1002/mus.10427

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  13 in total

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2.  Adaptive certainty-based classification for decomposition of EMG signals.

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Journal:  Med Biol Eng Comput       Date:  2006-03-23       Impact factor: 2.602

3.  The influence on sarcopenia of muscle quality and quantity derived from magnetic resonance imaging and neuromuscular properties.

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Journal:  Age (Dordr)       Date:  2014-06

4.  Motor unit number and transmission stability in octogenarian world class athletes: Can age-related deficits be outrun?

Authors:  Geoffrey A Power; Matti D Allen; Kevin J Gilmore; Daniel W Stashuk; Timothy J Doherty; Russell T Hepple; Tanja Taivassalo; Charles L Rice
Journal:  J Appl Physiol (1985)       Date:  2016-03-24

5.  Motor unit number estimation based on high-density surface electromyography decomposition.

Authors:  Yun Peng; Jinbao He; Bo Yao; Sheng Li; Ping Zhou; Yingchun Zhang
Journal:  Clin Neurophysiol       Date:  2016-06-25       Impact factor: 3.708

6.  Profiling age-related muscle weakness and wasting: neuromuscular junction transmission as a driver of age-related physical decline.

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Journal:  Geroscience       Date:  2021-04-24       Impact factor: 7.713

7.  Human motor unit characteristics of the superior trapezius muscle with age-related comparisons.

Authors:  Eric A Kirk; Kevin J Gilmore; Daniel W Stashuk; Timothy J Doherty; Charles L Rice
Journal:  J Neurophysiol       Date:  2019-06-26       Impact factor: 2.714

8.  Assessing motor deficits in compressive neuropathy using quantitative electromyography.

Authors:  Joseph Nashed; Andrew Hamilton-Wright; Daniel W Stashuk; Matthew Faris; Linda McLean
Journal:  J Neuroeng Rehabil       Date:  2010-08-11       Impact factor: 4.262

9.  Reliability of a modified motor unit number index (MUNIX) technique.

Authors:  Ryan D Kaya; Richard L Hoffman; Brian C Clark
Journal:  J Electromyogr Kinesiol       Date:  2013-10-16       Impact factor: 2.368

10.  Motor unit potential morphology differences in individuals with non-specific arm pain and lateral epicondylitis.

Authors:  Kristina M Calder; Daniel W Stashuk; Linda McLean
Journal:  J Neuroeng Rehabil       Date:  2008-12-16       Impact factor: 4.262

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