Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review
Irene Koenig,
Patric Eichelberger,
Angela Blasimann,
Antonia Hauswirth,
Jean-Pierre Baeyens and
Lorenz Radlinger
PLOS ONE, 2018, vol. 13, issue 11, 1-15
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 pre-and 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.
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0206549
DOI: 10.1371/journal.pone.0206549
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