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首页> 外文期刊>Journal of Biomechanics >Predicting human walking gaits with a simple planar model
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Predicting human walking gaits with a simple planar model

机译：用简单的平面模型预测人的步态

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摘要

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.
机译：具有中等复杂度的人步行模型具有潜在地准确捕获关节运动学和全身能量学的潜力，从而比非常简单的模型提供更多的同步信息，并且比非常复杂的模型提供更少的计算成本。这项工作研究了具有膝盖和刚性圆脚的四链接和六链接平面两足动物模型。两者的区别在于六链接模型包括脚踝关节。使用基于零动态的混合控制方法为两个模型生成稳定的周期性步态。为了建立模型可以近似正常人步行的基线，优化了步态以匹配实验人步行数据，速度从非常慢到非常快。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，而四连杆模型则不匹配，这表明脚踝工作是此类人体步行模型中的关键要素。除了简单地匹配人类数据外，六链接模型还可以在优化框架中用于使用扭矩平方目标函数预测正常的人类行走。该模型很好地预测了整个速度范围内的实验步长，关节运动和平均绝对功率。

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