A three‑dimensional whole‑body model to predict human walking on level ground

Dan Hu; David Howard; Lei Ren

doi:10.1007/s10237-022-01629-7

A three‑dimensional whole‑body model to predict human walking on level ground

Dan Hu, David Howard, Lei Ren

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3 Citations (Scopus)

66 Downloads (Pure)

Abstract

Predictive simulation of human walking has great potential in clinical motion analysis and rehabilitation engineering assessment, but large computational cost and reliance on measurement data to provide initial guess have limited its wide use. We developed a computationally efficient model combining optimization and inverse dynamics to predict three-dimensional whole-body motions and forces during human walking without relying on measurement data. Using the model, we explored two different optimization objectives, mechanical energy expenditure and the time integral of normalized joint torque. Of the two criteria, the sum of the time integrals of the normalized joint torques produced a more realistic walking gait. The reason for this difference is that most of the mechanical energy expenditure is in the sagittal plane (based on measurement data) and this leads to difficulty in prediction in the other two planes. We conclude that mechanical energy may only account for part of the complex performance criteria driving human walking in three dimensions.

Original language	English
Pages (from-to)	1919-1933
Number of pages	15
Journal	Biomechanics and Modeling in Mechanobiology
Volume	21
Issue number	6
Early online date	26 Oct 2022
DOIs	https://doi.org/10.1007/s10237-022-01629-7
Publication status	Published - Dec 2022

Bibliographical note

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Funder

Funding Information: This work was supported by the UK EPSRC by Grant nos. EP/I033602/1 and EP/K019759/1. This research was partly supported by the project of National Key R&D Program of China (No.2018YFC2001300), the project of National Natural Science Foundation of China (No.91948302, No.91848204, No.52005209, and No.51675222). Funding Information: This work was supported by the UK EPSRC by Grant nos. EP/I033602/1 and EP/K019759/1. Publisher Copyright: © 2022, The Author(s).

Funding

Funders	Funder number
Engineering and Physical Sciences Research Council	EP/K019759/1, EP/I033602/1
National Natural Science Foundation of China	52005209, 91848204, 51675222, 91948302
National Key Research and Development Program of China	2018YFC2001300

Keywords

Inverse dynamics
Locomotion
Optimization
Predictive models
Three-dimensional

ASJC Scopus subject areas

Biotechnology
Modelling and Simulation
Mechanical Engineering

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10.1007/s10237-022-01629-7Licence: CC BY

PublishedFinal published version, 2.03 MBLicence: CC BY

Cite this

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abstract = "Predictive simulation of human walking has great potential in clinical motion analysis and rehabilitation engineering assessment, but large computational cost and reliance on measurement data to provide initial guess have limited its wide use. We developed a computationally efficient model combining optimization and inverse dynamics to predict three-dimensional whole-body motions and forces during human walking without relying on measurement data. Using the model, we explored two different optimization objectives, mechanical energy expenditure and the time integral of normalized joint torque. Of the two criteria, the sum of the time integrals of the normalized joint torques produced a more realistic walking gait. The reason for this difference is that most of the mechanical energy expenditure is in the sagittal plane (based on measurement data) and this leads to difficulty in prediction in the other two planes. We conclude that mechanical energy may only account for part of the complex performance criteria driving human walking in three dimensions.",

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A three‑dimensional whole‑body model to predict human walking on level ground

Abstract

Bibliographical note

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Keywords

ASJC Scopus subject areas

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