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

JOURNAL OF BIOMECHANICS

卷:106

Article

Looft, John M.^1,2  Frey-Law, Laura A.² 

[1] Minneapolis VA Hlth Care Syst, Minneapolis, MN 55417 USA

[2] Univ Iowa, Dept Phys Therapy & Rehabil Sci, Iowa City, IA 52442 USA

关键词: Shoulder flexion;    Intermittent fatigue;    Modeling;    Endurance time;    Torque decline;   

DOI  :  10.1016/j.jbiomech.2020.109762

来源: Elsevier

【 摘 要 】

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.

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