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首页> 外文期刊>Journal of Biomechanics >Modification of a three-compartment muscle fatigue model to predict peak torque decline during intermittent tasks
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Modification of a three-compartment muscle fatigue model to predict peak torque decline during intermittent tasks

机译:修改三室肌肉疲劳模型,以预测间歇性任务期间的峰值扭矩下降

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摘要

This study aimed to test whether adding a rest recovery parameter, r, to the analytical three compartment controller (3CC) fatigue model (Xia and Frey Law, 2008) will improve fatigue estimates during intermittent contractions. The 3CC muscle fatigue model uses differential equations to predict the flow of muscle between three muscle states: Resting (M-R), Active (M-A), and Fatigued (M-F). This model uses a feedback controller to match the active state to target loads and two joint-specific parameters: F, fatigue rate controlling flow from active to fatigued compartments) and R, the recovery rate controlling flow from the fatigued to the resting compartments. This model does well to predict intensity-endurance time curves for sustained isometric tasks. However, previous studies find when rest intervals are present that the model over predicts fatigue. Intermittent rest periods would allow for the occurrence of subsequent reactive vasodilation and post-contraction hyperemia. We hypothesize a modified 3CC-r fatigue model will improve predictions of force decay during intermittent contractions with the addition of a rest recovery parameter, r, to augment recovery during rest intervals, representing muscle re-perfusion. A meta-analysis compiling intermittent fatigue data from 63 publications reporting decline in peak torque (% torque decline) were used for comparison. The original model over-predicted fatigue development from 19 to 29% torque decline; the addition of a rest multiplier significantly improved fatigue estimates to 6-10% torque decline. We conclude the addition of a rest multiplier to the three-compartment controller fatigue model provides a physiologically consistent modification for tasks involving rest intervals, resulting in improved estimates of muscle fatigue. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本研究旨在测试是否将休息恢复参数,R,分析三个隔间控制器(3CC)疲劳模型(夏和弗雷法,2008)进行了改善在间歇性收缩期间提高疲劳估计。 3CC肌疲劳模型使用微分方程来预测三个肌肉态之间的肌肉流动:休息(M-R),活性(M-A)和疲劳(M-F)。该模型使用反馈控制器将活动状态与目标负载匹配和两个关节特定参数:F,从活性到疲劳室的疲劳率控制流动,R,恢复速率控制从疲劳到静止室的流动。该模型适用于预测持续等距任务的强度耐力时间曲线。然而,先前的研究发现,当休息间隔时,这些模型预测疲劳。间歇休息时间将允许发生随后的反应性血管舒张和收缩后充血。我们假设修改的3CC-R疲劳模型将在间歇收缩期间改善力衰减的预测,以在休息间隔期间增加休息间隔期间增加恢复,代表肌肉再灌注。从63个出版物报告峰值扭矩(%扭矩下降)下降的间歇性疲劳数据用于比较。原模型过度预测疲劳发展从19%到29%的扭矩下降;添加速率乘法器显着提高了疲劳估计值为6-10%的扭矩下降。我们得出结论将剩余倍增器的添加到三室控制器疲劳模型提供了涉及休息间隔的任务的生理上一致的修改,从而改善了肌肉疲劳的估计。 (c)2018年elestvier有限公司保留所有权利。

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