Department of Biomedical Engineering (ND-20), Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
J Biomech. 2010 Apr 19;43(6):1055-60. doi: 10.1016/j.jbiomech.2009.12.012. Epub 2010 Jan 13.
Although humans have a large repertoire of potential movements, gait patterns tend to be stereotypical and appear to be selected according to optimality principles such as minimal energy. When applied to dynamic musculoskeletal models such optimality principles might be used to predict how a patient's gait adapts to mechanical interventions such as prosthetic devices or surgery. In this paper we study the effects of different performance criteria on predicted gait patterns using a 2D musculoskeletal model. The associated optimal control problem for a family of different cost functions was solved utilizing the direct collocation method. It was found that fatigue-like cost functions produced realistic gait, with stance phase knee flexion, as opposed to energy-related cost functions which avoided knee flexion during the stance phase. We conclude that fatigue minimization may be one of the primary optimality principles governing human gait.
尽管人类拥有大量潜在的运动模式，但步态模式往往是刻板的，似乎是根据最小能量等最优原则选择的。当将这些最优原则应用于动态肌肉骨骼模型时，它们可以用来预测患者的步态如何适应机械干预，如假肢或手术。在本文中，我们使用二维肌肉骨骼模型研究了不同性能标准对预测步态模式的影响。利用直接配置方法解决了一系列不同代价函数的最优控制问题。结果发现，类似于疲劳的代价函数产生了现实的步态，包括站立相膝关节屈曲，而与能量相关的代价函数则避免了站立相的膝关节屈曲。我们得出结论，疲劳最小化可能是控制人类步态的主要最优原则之一。
