Literature DB >> 33681763

Surface Electromyography Spectral Parameters for the Study of Muscle Fatigue in Swimming.

Luca Puce1, Ilaria Pallecchi2, Lucio Marinelli1,3, Laura Mori1,3, Marco Bove3,4, Daniele Diotti1, Piero Ruggeri4,5, Emanuela Faelli4,5, Filippo Cotellessa1, Carlo Trompetto1,3.   

Abstract

The purpose of this study was to assess validity, stability and sensitivity, of 4 spectral parameters-median frequency (Fmed), mean frequency (Fmean), Dimitrov index (DI), and mean instant frequency (Fmi)-in measuring localized muscle fatigue in swimming and to investigate their correlation with the variations of kinematic data and mechanical fatigue. Electrophysiological measures of muscle fatigue were obtained in real-time during a 100 m front crawl test at maximum speed in 15 experienced swimmers, using surface electromyography in six muscles employed in front crawl, while kinematic data of swimming was measured from video analysis. Mechanical fatigue was measured as the difference between muscle strength prior to and immediately after the 100 m front crawl in a dry-land multi-stage isometric contraction test. Statistically significant fatigue (p < 0.0001) was found for all spectral parameters in all muscles. Fmed and Fmean varied between 10 and 25%, DI between 50 and 150%, and Fmi between 5 and 10%. Strong correlation (Pearson r ≥ 0.5) with mechanical fatigue was found for all spectral parameters except for Fmi and it was strongest for Fmed and Fmean. From our study, it turns out that Fmed and Fmean are more valid and stable parameters to measure fatigue in swimming, while DI is more sensitive.
Copyright © 2021 Puce, Pallecchi, Marinelli, Mori, Bove, Diotti, Ruggeri, Faelli, Cotellessa and Trompetto.

Entities:  

Keywords:  electromyography; fatigue; master swimmers; spectral parameters; swimming; video analysis

Year:  2021        PMID: 33681763      PMCID: PMC7933468          DOI: 10.3389/fspor.2021.644765

Source DB:  PubMed          Journal:  Front Sports Act Living        ISSN: 2624-9367


  2 in total

1.  Muscle Fatigue and Swimming Efficiency in Behind and Lateral Drafting.

Authors:  Luca Puce; Karim Chamari; Lucio Marinelli; Laura Mori; Marco Bove; Emanuela Faelli; Marco Fassone; Filippo Cotellessa; Nicola Luigi Bragazzi; Carlo Trompetto
Journal:  Front Physiol       Date:  2022-03-03       Impact factor: 4.566

2.  A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue.

Authors:  Giovanni Corvini; Silvia Conforto
Journal:  Sensors (Basel)       Date:  2022-08-24       Impact factor: 3.847

  2 in total

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