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Adapting a fatigue model for shoulder flexion fatigue: Enhancing recovery rate during intermittent rest intervals
Journal article   Peer reviewed

Adapting a fatigue model for shoulder flexion fatigue: Enhancing recovery rate during intermittent rest intervals

John M. Looft and Laura A. Frey-Law
Journal of biomechanics, Vol.106, p.109762
06/09/2020
DOI: 10.1016/j.jbiomech.2020.109762
PMCID: PMC8848298
PMID: 32517992
url
https://www.ncbi.nlm.nih.gov/pmc/articles/8848298View
Open Access

Abstract

Although the rotator cuff muscles are susceptible to fatigue, shoulder fatigue studies reporting torque decline during intermittent tasks are relatively uncommon in the literature. A previous modification to the three-compartment controller (3CC) fatigue model incorporated a rest recovery multiplier (3CC-r model) to represent augmented blood flow to muscle during rest intervals (Looft et al., 2018). A rest recovery value of r = 15 was optimal for ankle, knee, and elbow joint regions, whereas r = 30 was better for hand/grip muscles. However, shoulder torque decline data was unavailable in the literature for comparison. Thus, the purpose of this study was to collect fatigue data for two different intermittent, isometric shoulder flexion fatiguing tasks and assess the 3CC-r model with r = 15 or 30 compared to the original 3CC model. Twenty healthy participants (9 M) completed two fatigue tasks: 50% maximum voluntary contraction (MVC) with 50% duty cycle (DC) and 70% MVC with 70% DC. MVCs were assessed at discrete time points (1, 3, 5, 10, and 15 min) until endurance time (MET). Mean observed percent torque decline (% TD) for the two tasks were compared to three model estimates: 3CC-r (using r = 15 and r = 30) and 3CC. Using these data, we confirmed that the addition of a rest multiplier (r = 15 somewhat better than r = 30) substantially improved predictions of shoulder fatigue using a previously validated analytical fatigue model (3CC). The relatively large reduction in model errors over the original model suggests the importance of representing augmented recovery during rest periods. Published by Elsevier Ltd.
Biophysics Engineering Engineering, Biomedical Life Sciences & Biomedicine Science & Technology Technology

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