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Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running

Tools have been used for millions of years to augment the capabilities of the human body, allowing us to accomplish tasks that would otherwise be difficult or impossible. Powered exoskeletons and other assistive devices are sophisticated modern tools that have restored bipedal locomotion in individu...

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Autores principales: Uchida, Thomas K., Seth, Ajay, Pouya, Soha, Dembia, Christopher L., Hicks, Jennifer L., Delp, Scott L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5033584/
https://www.ncbi.nlm.nih.gov/pubmed/27656901
http://dx.doi.org/10.1371/journal.pone.0163417
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author Uchida, Thomas K.
Seth, Ajay
Pouya, Soha
Dembia, Christopher L.
Hicks, Jennifer L.
Delp, Scott L.
author_facet Uchida, Thomas K.
Seth, Ajay
Pouya, Soha
Dembia, Christopher L.
Hicks, Jennifer L.
Delp, Scott L.
author_sort Uchida, Thomas K.
collection PubMed
description Tools have been used for millions of years to augment the capabilities of the human body, allowing us to accomplish tasks that would otherwise be difficult or impossible. Powered exoskeletons and other assistive devices are sophisticated modern tools that have restored bipedal locomotion in individuals with paraplegia and have endowed unimpaired individuals with superhuman strength. Despite these successes, designing assistive devices that reduce energy consumption during running remains a substantial challenge, in part because these devices disrupt the dynamics of a complex, finely tuned biological system. Furthermore, designers have hitherto relied primarily on experiments, which cannot report muscle-level energy consumption and are fraught with practical challenges. In this study, we use OpenSim to generate muscle-driven simulations of 10 human subjects running at 2 and 5 m/s. We then add ideal, massless assistive devices to our simulations and examine the predicted changes in muscle recruitment patterns and metabolic power consumption. Our simulations suggest that an assistive device should not necessarily apply the net joint moment generated by muscles during unassisted running, and an assistive device can reduce the activity of muscles that do not cross the assisted joint. Our results corroborate and suggest biomechanical explanations for similar effects observed by experimentalists, and can be used to form hypotheses for future experimental studies. The models, simulations, and software used in this study are freely available at simtk.org and can provide insight into assistive device design that complements experimental approaches.
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spelling pubmed-50335842016-10-10 Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running Uchida, Thomas K. Seth, Ajay Pouya, Soha Dembia, Christopher L. Hicks, Jennifer L. Delp, Scott L. PLoS One Research Article Tools have been used for millions of years to augment the capabilities of the human body, allowing us to accomplish tasks that would otherwise be difficult or impossible. Powered exoskeletons and other assistive devices are sophisticated modern tools that have restored bipedal locomotion in individuals with paraplegia and have endowed unimpaired individuals with superhuman strength. Despite these successes, designing assistive devices that reduce energy consumption during running remains a substantial challenge, in part because these devices disrupt the dynamics of a complex, finely tuned biological system. Furthermore, designers have hitherto relied primarily on experiments, which cannot report muscle-level energy consumption and are fraught with practical challenges. In this study, we use OpenSim to generate muscle-driven simulations of 10 human subjects running at 2 and 5 m/s. We then add ideal, massless assistive devices to our simulations and examine the predicted changes in muscle recruitment patterns and metabolic power consumption. Our simulations suggest that an assistive device should not necessarily apply the net joint moment generated by muscles during unassisted running, and an assistive device can reduce the activity of muscles that do not cross the assisted joint. Our results corroborate and suggest biomechanical explanations for similar effects observed by experimentalists, and can be used to form hypotheses for future experimental studies. The models, simulations, and software used in this study are freely available at simtk.org and can provide insight into assistive device design that complements experimental approaches. Public Library of Science 2016-09-22 /pmc/articles/PMC5033584/ /pubmed/27656901 http://dx.doi.org/10.1371/journal.pone.0163417 Text en © 2016 Uchida et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Uchida, Thomas K.
Seth, Ajay
Pouya, Soha
Dembia, Christopher L.
Hicks, Jennifer L.
Delp, Scott L.
Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title_full Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title_fullStr Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title_full_unstemmed Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title_short Simulating Ideal Assistive Devices to Reduce the Metabolic Cost of Running
title_sort simulating ideal assistive devices to reduce the metabolic cost of running
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5033584/
https://www.ncbi.nlm.nih.gov/pubmed/27656901
http://dx.doi.org/10.1371/journal.pone.0163417
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