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Utility of traditional and alternative EMG-based measures of fatigue during low-moderate level isometric efforts.
J Electromyogr Kinesiol 2008 Feb; 18(1):44-53
Most existing evidence regarding the effects of age on muscular fatigue has focused on prolonged isometric contractions, repeated maximum dynamic contractions and individuals beyond traditional retirement age (465 years). In the present study, age-related differences in muscle fatigue during submaximal dynamic efforts were examined. There were 24 younger (18-25 years) and 24 older (55-65 years) participants, all of whom were healthy and active, with equal numbers of each gender within each age group. Participants performed repetitive, intermittent shoulder abductions until exhaustion, at peak moments of 30% and 40% of individual maximum voluntary isokinetic contraction (MVIC) and with cycle durations of 20 and 40 s. Fatigue development was determined based on changes in MVIC, electromyographic (EMG) signals and ratings of perceived discomfort (RPD). Following the exhaustive exercises, strength recovery was monitored using a series of MVICs over a 15-min period. Results indicated the existence of an age-related fatigue resistance, with the older group demonstrating significantly slower rates of MVIC decline and RPD increase and smaller modifications in EMG-based fatigue measures. These age effects were generally more pronounced at the higher effort level. Main effects of effort level and cycle duration were also significant, while gender effects appeared to be marginal. Rates of strength recovery were not significantly influenced by age. In addition, the utility of standard EMG-based fatigue measures was assessed. Findings indicated that time-dependent changes in static and dynamic EMG-based measures were roughly comparable in terms of sensitivity and variability, supporting the use of standard EMG analyses for fatigue monitoring during intermittent dynamic contractions.
Statistical-analysis; Ergonomics; Physical-stress; Physical-exercise; Musculoskeletal-system; Muscles; Muscle-stress; Muscle-tension; Muscular-disorders; Age-factors; Electrophysiological-measurements; Fatigue; Genetic-factors
Maury A. Nussbaum, Department of Industrial and Systems Engineering, School of Biomedical Engineering and Sciences, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061
Grant; Cooperative Agreement
Issue of Publication
Journal of Electromyography and Kinesiology
Virginia Polytechnic Institute and State University
Page last reviewed: April 12, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division