Aerospace and Mechanical Engineering, University of Notre Dame, South Bend, IN, USA.
J Biomech. 2014 Apr 11;47(6):1416-21. doi: 10.1016/j.jbiomech.2014.01.035. Epub 2014 Feb 7.
Models of human walking with moderate complexity have the potential to accurately capture both joint kinematics and whole body energetics, thereby offering more simultaneous information than very simple models and less computational cost than very complex models. This work examines four- and six-link planar biped models with knees and rigid circular feet. The two differ in that the six-link model includes ankle joints. Stable periodic walking gaits are generated for both models using a hybrid zero dynamics-based control approach. To establish a baseline of how well the models can approximate normal human walking, gaits were optimized to match experimental human walking data, ranging in speed from very slow to very fast. The six-link model well matched the experimental step length, speed, and mean absolute power, while the four-link model did not, indicating that ankle work is a critical element in human walking models of this type. Beyond simply matching human data, the six-link model can be used in an optimization framework to predict normal human walking using a torque-squared objective function. The model well predicted experimental step length, joint motions, and mean absolute power over the full range of speeds.
具有中等复杂度的人类行走模型有可能准确地捕捉关节运动学和整个身体的能量学，从而提供比非常简单的模型更多的同步信息，同时计算成本也比非常复杂的模型低。这项工作研究了具有膝关节和刚性圆形脚的四连杆和六连杆平面步行模型。这两种模型的区别在于，六连杆模型包括踝关节。使用混合零动态控制方法为两种模型生成稳定的周期性步行步态。为了建立模型能够很好地近似正常人类行走的基准，步态被优化以匹配实验人类行走数据，速度范围从非常慢到非常快。六连杆模型很好地匹配了实验的步长、速度和平均绝对功率，而四连杆模型则没有，这表明踝关节的工作是这种类型的人类行走模型的一个关键要素。六连杆模型不仅可以简单地匹配人类数据，还可以在优化框架中使用扭矩平方目标函数来预测正常人类行走。该模型很好地预测了实验中的步长、关节运动和平均绝对功率，涵盖了所有速度范围。
