Claremont McKenna College, W.M. Keck Science Department, Claremont, California, United States of America.
Massachusetts Institute of Technology, MultiScale Materials Science for Energy and Environment, Joint MIT-CNRS Laboratory (UMI 3466), Cambridge, Massachusetts, United States of America.
PLoS One. 2018 Nov 16;13(11):e0206645. doi: 10.1371/journal.pone.0206645. eCollection 2018.
Models for human running performances of various complexities and underlying principles have been proposed, often combining data from world record performances and bio-energetic facts of human physiology. The purpose of this work is to develop a novel, minimal and universal model for human running performance that employs a relative metabolic power scale. The main component is a self-consistency relation for the time dependent maximal power output. The analytic approach presented here is the first to derive the observed logarithmic scaling between world (and other) record running speeds and times from basic principles of metabolic power supply. Our hypothesis is that various female and male record performances (world, national) and also personal best performances of individual runners for distances from 800m to the marathon are excellently described by this model. Indeed, we confirm this hypothesis with mean errors of (often much) less than 1%. The model defines endurance in a way that demonstrates symmetry between long and short racing events that are separated by a characteristic time scale comparable to the time over which a runner can sustain maximal oxygen uptake. As an application of our model, we derive personalized characteristic race speeds for different durations and distances.
已经提出了各种复杂程度的人类跑步表现模型和潜在原理,这些模型通常结合了世界纪录表现和人类生理学的生物能量事实的数据。本工作的目的是开发一种新颖、最小和通用的人类跑步表现模型,该模型采用相对代谢功率尺度。主要组成部分是一个随时间变化的最大功率输出的自洽关系。这里提出的分析方法是第一个从代谢功率供应的基本原理推导出世界纪录(和其他)跑步速度和时间之间观察到的对数比例关系。我们的假设是,各种女性和男性的世界纪录表现(世界纪录、国家纪录)以及个别跑步者的个人最佳表现,从 800 米到马拉松的各种距离,都可以通过该模型很好地描述。事实上,我们用(通常大大)小于 1%的平均误差来验证这个假设。该模型以一种方式定义耐力,展示了长距离和短距离比赛之间的对称性,它们由一个与跑步者能够维持最大摄氧量的时间相当的特征时间尺度隔开。作为我们模型的一个应用,我们推导出了不同持续时间和距离的个性化特征比赛速度。