J Matt McCrary1, Bronwen J Ackermann2, Mark Halaki3. 1. School of Medical Sciences, Sydney Medical School, The University of Sydney, Australia; Prince of Wales Clinical School, UNSW, Australia. Electronic address: j.mccrary@unsw.edu.au. 2. School of Medical Sciences, Sydney Medical School, The University of Sydney, Australia. 3. Discipline of Exercise and Sport Science, The University of Sydney, Australia.
Abstract
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.
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.