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  4. Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review.
 

Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review.

URI
https://arbor.bfh.ch/handle/arbor/39698
Version
Published
Date Issued
2018-11-02
Author(s)
Koenig, Irene
Eichelberger, Patric  
Blasimann Schwarz, Angela  
Hauswirth, Antonia
Baeyens, Jean-Pierre
Radlinger, Lorenz  
Type
Article
Language
English
Abstract
Surface electromyography is often used to assess muscle activity and muscle function. A
wavelet approach provides information about the intensity of muscle activity and motor unit
recruitment strategies at every time point of the gait cycle. The aim was to review papers
that employed wavelet analyses to investigate electromyograms of lower extremity muscles
during walking and running. Eleven databases were searched up until June 1st 2017. The
composition was based on the PICO model and the PRISMA checklist. First author, year,
subject characteristics, intervention, outcome measures & variables, results and wavelet
specification were extracted. Eighteen studies included the use of wavelets to investigate
electromyograms of lower extremity muscles. Three main topics were discussed: 1.) The
capability of the method to correctly assign participants to a specific group (recognition rate)
varied between 68.4%-100%. 2.) Patients with ankle osteoarthritis or total knee arthroplasty
presented a delayed muscle activation in the early stance phase but a prolonged activation
in mid stance. 3.) Atrophic muscles did not contain type II muscle fiber components but
more energy in their lower frequencies. The simultaneous information of time, frequency
and intensity is of high clinical relevance because it offers valuable information about preand
reflex activation behavior on different walking and running speeds as well as spectral
changes towards high or low frequencies at every time point of the gait cycle.
DOI
10.24451/arbor.6682
https://doi.org/10.24451/arbor.6682
Publisher DOI
10.1371/journal.pone.0206549
Journal
PLoS One
ISSN
1932-6203
Organization
Gesundheit  
Physiotherapie  
Beckenboden und Kontinenz  
Volume
13
Issue
11
Publisher
Public Library of Science (PLoS)
Submitter
ServiceAccount
Citation apa
Koenig, I., Eichelberger, P., Blasimann Schwarz, A., Hauswirth, A., Baeyens, J.-P., & Radlinger, L. (2018). Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review. In PLoS One (Vol. 13, Issue 11). Public Library of Science (PLoS). https://doi.org/10.24451/arbor.6682
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