首页> 美国卫生研究院文献>Proceedings of the Royal Society B: Biological Sciences >Evaluation of the minimum energy hypothesis and other potential optimality criteria for human running
【2h】

Evaluation of the minimum energy hypothesis and other potential optimality criteria for human running

机译:评估人类最低能量假设和其他潜在的最佳标准

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

A popular hypothesis for human running is that gait mechanics and muscular activity are optimized in order to minimize the cost of transport (CoT). Humans running at any particular speed appear to naturally select a stride length that maintains a low CoT when compared with other possible stride lengths. However, it is unknown if the nervous system prioritizes the CoT itself for minimization, or if some other quantity is minimized and a low CoT is a consequential effect. To address this question, we generated predictive computer simulations of running using an anatomically inspired musculoskeletal model and compared the results with data collected from human runners. Three simulations were generated by minimizing the CoT, the total muscle activation or the total muscle stress, respectively. While all the simulations qualitatively resembled real human running, minimizing activation predicted the most realistic joint angles and timing of muscular activity. While minimizing the CoT naturally predicted the lowest CoT, minimizing activation predicted a more realistic CoT in comparison with the experimental mean. The results suggest a potential control strategy centred on muscle activation for economical running.
机译:关于人类跑步的一个普遍假设是,步态力学和肌肉活动得到了优化,以最大程度地降低运输成本(CoT)。与其他可能的步长相比,以任何特定速度奔跑的人似乎自然会选择保持较低CoT的步长。但是,尚不清楚神经系统是否优先考虑CoT本身以使其最小化,或者其他一些数量是否被最小化以及低CoT的后果。为了解决这个问题,我们使用解剖学上受启发的肌肉骨骼模型生成了跑步的预测计算机模拟,并将结果与​​从跑步者那里收集的数据进行了比较。分别通过最小化CoT,总肌肉激活或总肌肉压力来生成三个模拟。虽然所有模拟在质量上都类似于真实的人类跑步,但最小化激活可以预测最现实的关节角度和肌肉活动的时机。与实验平均值相比,最小化CoT自然可以预测最低的CoT,而最小化激活则可以预测更现实的CoT。结果表明潜在的控制策略集中在肌肉激活上,以实现经济运行。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号