A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait
A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait
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DOI：
10.1080/10255842.2018.1490954
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发表时间：
2018-01-01
影响因子：
1.6
通讯作者：
van den Bogert, Antonie J.
中科院分区：
文献类型：
--
作者：
Koelewijn, Anne D.;Dorschky, Eva;van den Bogert, Antonie J.
人类是否在步态中最小化代谢能量尚不清楚。基于顺应性的优化可以用于预测步态，而不使用步行数据，但需要一个二次可微的代谢能量模型。因此，Umberger埃塔尔.（2003）被修改为二次可微。使用该连续模型并通过最小化努力来解决达到任务和步态的预测模拟。达到任务模拟表明，能量最小化预测不切实际的运动相比，努力最小化。预测步态模拟表明，目标以外的代谢能量也很重要的步态。
Whether humans minimize metabolic energy in gait is unknown. Gradient-based optimization could be used to predict gait without using walking data but requires a twice differentiable metabolic energy model. Therefore, the metabolic energy model of Umberger etal. (2003) was adapted to be twice differentiable. Predictive simulations of a reaching task and gait were solved using this continuous model and by minimizing effort. The reaching task simulation showed that energy minimization predicts unrealistic movements when compared to effort minimization. The predictive gait simulations showed that objectives other than metabolic energy are also important in gait.