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Optimization of energy and time predicts dynamic speeds for human walking

Humans make a number of choices when they walk, such as how fast and for how long. The preferred steady walking speed seems chosen to minimize energy expenditure per distance traveled. But the speed of actual walking bouts is not only steady, but rather a time-varying trajectory, which can also be m...

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Detalles Bibliográficos
Autores principales: Carlisle, Rebecca Elizabeth, Kuo, Arthur D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030114/
https://www.ncbi.nlm.nih.gov/pubmed/36779697
http://dx.doi.org/10.7554/eLife.81939
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author Carlisle, Rebecca Elizabeth
Kuo, Arthur D
author_facet Carlisle, Rebecca Elizabeth
Kuo, Arthur D
author_sort Carlisle, Rebecca Elizabeth
collection PubMed
description Humans make a number of choices when they walk, such as how fast and for how long. The preferred steady walking speed seems chosen to minimize energy expenditure per distance traveled. But the speed of actual walking bouts is not only steady, but rather a time-varying trajectory, which can also be modulated by task urgency or an individual’s movement vigor. Here we show that speed trajectories and durations of human walking bouts are explained better by an objective to minimize Energy and Time, meaning the total work or energy to reach destination, plus a cost proportional to bout duration. Applied to a computational model of walking dynamics, this objective predicts dynamic speed vs. time trajectories with inverted U shapes. Model and human experiment (N=10) show that shorter bouts are unsteady and dominated by the time and effort of accelerating, and longer ones are steadier and faster and dominated by steady-state time and effort. Individual-dependent vigor may be characterized by the energy one is willing to spend to save a unit of time, which explains why some may walk faster than others, but everyone may have similar-shaped trajectories due to similar walking dynamics. Tradeoffs between energy and time costs can predict transient, steady, and vigor-related aspects of walking.
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spelling pubmed-100301142023-03-22 Optimization of energy and time predicts dynamic speeds for human walking Carlisle, Rebecca Elizabeth Kuo, Arthur D eLife Computational and Systems Biology Humans make a number of choices when they walk, such as how fast and for how long. The preferred steady walking speed seems chosen to minimize energy expenditure per distance traveled. But the speed of actual walking bouts is not only steady, but rather a time-varying trajectory, which can also be modulated by task urgency or an individual’s movement vigor. Here we show that speed trajectories and durations of human walking bouts are explained better by an objective to minimize Energy and Time, meaning the total work or energy to reach destination, plus a cost proportional to bout duration. Applied to a computational model of walking dynamics, this objective predicts dynamic speed vs. time trajectories with inverted U shapes. Model and human experiment (N=10) show that shorter bouts are unsteady and dominated by the time and effort of accelerating, and longer ones are steadier and faster and dominated by steady-state time and effort. Individual-dependent vigor may be characterized by the energy one is willing to spend to save a unit of time, which explains why some may walk faster than others, but everyone may have similar-shaped trajectories due to similar walking dynamics. Tradeoffs between energy and time costs can predict transient, steady, and vigor-related aspects of walking. eLife Sciences Publications, Ltd 2023-02-13 /pmc/articles/PMC10030114/ /pubmed/36779697 http://dx.doi.org/10.7554/eLife.81939 Text en © 2023, Carlisle and Kuo https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Carlisle, Rebecca Elizabeth
Kuo, Arthur D
Optimization of energy and time predicts dynamic speeds for human walking
title Optimization of energy and time predicts dynamic speeds for human walking
title_full Optimization of energy and time predicts dynamic speeds for human walking
title_fullStr Optimization of energy and time predicts dynamic speeds for human walking
title_full_unstemmed Optimization of energy and time predicts dynamic speeds for human walking
title_short Optimization of energy and time predicts dynamic speeds for human walking
title_sort optimization of energy and time predicts dynamic speeds for human walking
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030114/
https://www.ncbi.nlm.nih.gov/pubmed/36779697
http://dx.doi.org/10.7554/eLife.81939
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