Markowitz Jared, Herr Hugh
MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS Comput Biol. 2016 May 13;12(5):e1004912. doi: 10.1371/journal.pcbi.1004912. eCollection 2016 May.
Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle.
人类在关节驱动中采用了高度冗余的方式，不同的肌肉和肌腱作用组合可提供相同的净关节扭矩。这些冗余的解决方式以及此类系统的能量学都取决于肌肉和肌腱的动态特性，尤其是它们的力-长度关系。当前在模拟肌肉-肌腱动力学时使用固定参数的行走模型往往会显著高估代谢消耗，这可能是因为它们没有充分考虑弹性的作用。作为一种替代方法，我们假定人类腿部的肌肉-肌腱形态已经进化，以在自选速度下行走时使代谢效率最大化。我们采用数据驱动的方法来评估这一假设，利用从五名以自选速度行走的参与者身上获取的运动学、动力学、肌电图（EMG）和代谢数据。运动学和动力学数据用于估计肌肉-肌腱长度、肌肉力臂和关节力矩，而EMG数据用于估计肌肉激活情况。对于每个受试者，我们使用规定的骨骼运动学进行优化，改变控制每条肌腱力-长度曲线的参数以及每条肌肉的强度和最佳纤维长度，同时力求在最小化代谢成本的同时，最大化与估计关节力矩的一致性。我们发现，通过对肌肉代谢预算施加单一约束，我们参与者的运输代谢成本（MCOT）值可以得到正确匹配（平均预测值为0.36±0.02，测量值为0.35±0.02），并且关节扭矩保真度可接受。相关的最佳肌肉-肌腱参数集使我们能够估计单个肌肉的力和状态，解决关节驱动中的冗余问题，并深入了解整个步态周期中腿部肌肉的潜在作用和控制目标。
