柔性与刚性肌腱模型:精度、计算效率和数值稳定性的仿真研究

A. Mousavi, H. Ehsani, M. Rostami
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引用次数: 3

摘要

提供一个兼顾计算效率和精度的高效的骨骼肌数学模型是多肌肉问题仿真的关键因素。以往的研究表明,当肌腱松弛长度与肌肉最佳长度之比小于等于1时,忽略肌腱的弹性特性可以减少模拟的时间成本,但会引入一些小误差。本文的目的是测试该准则在人体肌肉通常长度运动中的精度、效率和数值稳定性。在这方面,我们选择了人体上肢的两块肌肉(肱桡肌(BRD)二头肌(BICL))和下肢的一块肌肉(比目鱼肌(SOL))。本研究考虑了一般Hill-based肌肌腱模型的两种变体。在第一个模型中,使用非线性弹簧将肌腱的弹性特性纳入模型,而在第二个模型中,忽略这一特性,假设肌腱的长度为恒定。BRD、BICL和SOL模型的力分布平均绝对误差分别为4.2、12和13.1。使用隐式积分器,刚性肌腱模型比柔性肌腱模型快7.3 ~ 9.5倍。对于BRD,两种模型的结果具有相似的趋势,并且力分布之间的差异可以忽略不计。然而,从柔顺肌腱模型得到的结果说明了一些数值稳定性问题。在第二个肌肉,即BICL,同样BRD,力剖面的趋势是相同的;然而,两种模式的结果差距已经扩大。与BRD类似,刚性肌腱模型所需的计算时间更少。检查为SOL获得的结果,可以很容易地发现两个模型的结果之间的显著差异。考虑到上述三个肌腱单元的肌腱松弛长度与最佳肌长之比,可以得出这样的结论:当该值小于1时,建议使用刚性肌腱模型。如果该值不大于1,如BICL,则利用刚性肌腱模型将提高计算效率,但代价是结果会受到一些误差的污染。然而,如果这一比例远不一致,如SOL,则不建议忽略肌腱的长度变化。
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Compliant Vs. rigid tendon models: A simulation study on precision, computational efficiency and numerical stability
Providing an efficient mathematical model of the skeletal muscles which takes both computational efficiency and accuracy into account is a crucial factor in the simulations of multiple-muscle problems. Previous studies stated that ignoring the elastic characteristics of the tendon can reduce the time cost of simulations at the expense of introducing some minor errors if the ratio of tendon slack length to muscle optimum length is less than or equal to unity. The purpose of this paper was to test the precision, efficiency and numerical stability of this criterion for the muscles of the human body in their usual length excursions. In this regard two muscles of the upper extremity (Brachioradialis (BRD) long head of biceps (BICL)) and one from the lower extremity (soleus (SOL)) of the human body have been chosen. Two variations of a general Hill-based musculotendon model have been considered in this study. In the first one, using a nonlinear spring the elastic properties of the tendon has been incorporated into the model and in the second one, ignoring this properties, a constant length for the tendon has been assumed. The mean absolute error between the force profiles of the two models for BRD, BICL and SOL were 4.2, 12 and 13.1 respectively. Also rigid-tendon model was 7.3 to 9.5 times faster than compliant-tendon model using the implicit integrator. For BRD the outcomes of the two models, have similar trends and the discrepancies between the force profiles are negligible. However, the results obtained from the compliant-tendon model illustrate some numerical stability problems. In the second muscle, i.e. BICL, likewise BRD the trends of the force profiles are the same; however, the disparity among the outcomes of the two models have escalated. Likewise BRD, the rigid-tendon model required less computational time. Inspecting the results obtained for SOL, one can easily spot the significant differences between the outcomes of the two models. Considering the tendon slack length to the optimum muscle length ratio for the three mentioned musculotendon units, one can draw this conclusion that, in case this value is less than unity using the rigid-tendon model is recommended. If this value is not much greater than unity, like BICL, exploiting the rigid-tendon model will increase the computational efficiency in expense of contaminating the outcomes with some amounts of error. However, if this ratio is far from unity, like SOL, ignoring the length alterations in the tendon is not recommended.
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