EMG amplitude, fatigue threshold, and time to task failure: A meta-analysis.

Objectives: Electromyographic (EMG) fatigue threshold (EMGFT) is utilised as a correlate of critical power, torque, and force thresholds that establishes a theoretical exercise intensity-the power, torque, or force at which the rate of change of EMG amplitude (ΔEM¯G) is zero-below which neuromuscula...

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Publicado en:Journal of Science & Medicine in Sport Vol. 21; no. 7; pp. 736 - 742
Autores principales: McCrary, J. Matt, Ackermann, Bronwen J., Halaki, Mark
Formato: meta analysis research systematic review Journal Article
Publicado: Elsevier B.V. Jul2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2018
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      pub: Elsevier B.V.
      place: New York, New York
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        10.1016/j.jsams.2017.11.005
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      tig:
        atl: EMG amplitude, fatigue threshold, and time to task failure: A meta-analysis.
      aug:
        au:
          McCrary, J. Matt
          Ackermann, Bronwen J.
          Halaki, Mark
        affil: School of Medical Sciences, Sydney Medical School, The University of Sydney, Australia
      sug:
        subj:
          Electromyography
          Muscle, Skeletal Physiology
          Muscle Fatigue
          Human
          Isometric Contraction
          Linear Regression
          Meta Analysis
          Systematic Review
      ab: Objectives: Electromyographic (EMG) fatigue threshold (EMGFT) is utilised as a correlate of critical power, torque, and force thresholds that establishes a theoretical exercise intensity-the power, torque, or force at which the rate of change of EMG amplitude (ΔEM¯G) is zero-below which neuromuscular fatigue is negligible and unpredictable. Recent studies demonstrating neuromuscular fatigue below critical thresholds raise questions about the construct validity of EMGFT. The purpose of this analysis is to evaluate the construct validity of EMGFT by aggregating ΔEM¯G and time to task failure (Tlim) data.Design: Meta-analysis.Methods: Database search of MEDLINE, SPORTDiscus, Web of Science, and Cochrane (inception - September 2016) conducted using terms relevant to EMG and muscle fatigue. Inclusion criteria were studies reporting agonist muscle EMG amplitude data during constant force voluntary isometric contractions taken to task failure. Linear and nonlinear regression models were used to relate ΔEM¯G and Tlim data extracted from included studies.Results: Regression analyses included data from 837 healthy adults from 43 studies. Relationships between ΔEM¯G and Tlim were strong in both nonlinear (R2=0.65) and linear (R2=0.82) models. ΔEM¯G at EMGFT was significantly nonzero overall and in 3 of 5 cohorts in the nonlinear model (p<0.01) and in 2 of 5 cohorts in the linear model.Conclusions: EMGFT lacks face validity as currently calculated; models for more precise EMGFT calculation are proposed. A new framework for prediction of task failure using EMG amplitude data alone is presented. The ΔEM¯G vs. Tlim relationship remains consistent across sexes and force vs. position tasks.
      pubtype: Academic Journal
      doctype:
        meta analysis
        research
        systematic review
        Journal Article
      ougenre: Article
    language: English
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