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Analytic analysis of the force sharing among synergistic muscles in one- and two-degree-of-freedom models

机译:一自由度和两自由度模型中协同肌肉之间的力共享分析分析

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Mathematical optimization of specific cost functions has been used in theoretical models to calculate individual muscle forces. Measurements of individual muscle forces and force sharing among individual muscles show an intensity-dependent, non-linear behavior. It has been demonstrated that the force sharing between the cat Gastrocnemius, Plantaris and Soleus shows distinct loops that change orientation systematically depending on the intensity of the movement. The purpose of this study was to prove whether or not static, non-linear optimization could inherently predict force sharing loops between agonistic muscles. Using joint moment data from a step cycle of cat locomotion, the forces in three cat ankle plantar flexors (Gastrocnemius, Plantaris and Soleus) were calculated using two popular optimization algorithms and two musculo-skeletal models. The two musculo-skeletal models included a one-degree-of-freedom model that considered the ankle joint exclusively and a two-degree-of-freedom model that included the ankle and the knee joint. The main conclusion of this study was that solutions of the one-degree-of-freedom model do not guarantee force-sharing loops, but the two-degree-of-freedom model predicts force-sharing loops independent of the specific values of the input parameters for the muscles and the musculo-skeletal geometry. The predicted force-sharing loops were found to be a direct result of the loops formed by the knee and ankle moments in a moment-moment graph. (C) 2000 Elsevier Science Ltd. All rights reserved. [References: 19]
机译:在理论模型中已使用特定成本函数的数学优化来计算单个肌肉力。对单个肌肉力和单个肌肉之间的力共享的测量显示出强度相关的非线性行为。事实证明,猫腓肠肌,Plant足肌和Soleus之间的分担力显示出不同的环,这些环根据运动的强度来系统地改变方向。这项研究的目的是证明静态,非线性优化是否可以固有地预测激动性肌肉之间的力共享回路。使用来自猫运动阶跃周期的联合力矩数据,使用两种流行的优化算法和两个肌肉骨骼模型计算了三个猫踝踝关节屈肌(腓肠肌,足底肌和足肌)的力。这两个肌肉骨骼模型包括一个仅考虑踝关节的单自由度模型,以及一个包含踝关节和膝关节的两自由度模型。这项研究的主要结论是,一自由度模型的解决方案不能保证力共享环,但是二自由度模型可以预测力共享环,而与输入的特定值无关肌肉和肌肉骨骼几何参数。发现预测的力共享回路是由力矩矩图中的膝盖和踝部力矩形成的回路的直接结果。 (C)2000 Elsevier ScienceLtd。保留所有权利。 [参考:19]

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