Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading.
Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading.
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DOI：
10.1016/j.jbiomech.2010.05.036
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发表时间：
2010-10-19
影响因子：
2.4
通讯作者：
van den Bogert, Antonie J.
中科院分区：
文献类型：
--
作者：
Halloran, Jason P.;Ackermann, Marko;Erdemir, Ahmet;van den Bogert, Antonie J.
关键词：
当前用于模拟运动的计算方法主要使用肌肉驱动的多体动力学，其中神经肌肉控制被优化。为了提高计算效率，此类模拟通常将关节和软组织表示为简单的运动学或弹性元件。这些假设限制了在韧带损伤或骨关节炎等必须预测局部组织负荷的研究中的应用。相反，可以使用有限元方法在假设或测量的边界条件下模拟组织，但这并不代表全身动力学和神经肌肉控制的效果。将两个域耦合将克服这些限制，并允许预测由组织应力引导的运动策略。在这里，我们在步态模拟中演示了这个概念，其中肌肉骨骼模型与足部的有限元表示耦合。预测模拟将足底组织变形峰值纳入运动优化的目标，以及跟踪规范步态数据和最大限度减少疲劳的术语。进行了两次优化，第一次没有应变最小化项，第二次有该项。实现了与现实步态模式的收敛，第二次优化实现了峰值组织应变能密度降低了 44%。该研究表明，可以改变计算预测的神经肌肉控制，以最大限度地减少组织应变，同时包括所需的运动学和肌肉行为。未来的工作应包括在将该方法应用于患者护理之前进行实验验证。
Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved, with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation, before application of the methodology to patient care.
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DOI：
10.1115/1.1634282
发表时间：
2003-12-01
影响因子：
1.7
作者：
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影响因子：
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影响因子：
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作者：
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通讯作者：
van den Bogert, Antonie J.
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