Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.

Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate withi...

Full description

Bibliographic Details
Main Authors: Arash Mohammadzadeh Gonabadi, Prokopios Antonellis, Philippe Malcolm
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-10-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1008280
_version_ 1819045141600534528
author Arash Mohammadzadeh Gonabadi
Prokopios Antonellis
Philippe Malcolm
author_facet Arash Mohammadzadeh Gonabadi
Prokopios Antonellis
Philippe Malcolm
author_sort Arash Mohammadzadeh Gonabadi
collection DOAJ
description Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle.
first_indexed 2024-12-21T10:23:51Z
format Article
id doaj.art-aad3b6256ea246f284b7f70556ecefb3
institution Directory Open Access Journal
issn 1553-734X
1553-7358
language English
last_indexed 2024-12-21T10:23:51Z
publishDate 2020-10-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS Computational Biology
spelling doaj.art-aad3b6256ea246f284b7f70556ecefb32022-12-21T19:07:22ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-10-011610e100828010.1371/journal.pcbi.1008280Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.Arash Mohammadzadeh GonabadiProkopios AntonellisPhilippe MalcolmMotion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle.https://doi.org/10.1371/journal.pcbi.1008280
spellingShingle Arash Mohammadzadeh Gonabadi
Prokopios Antonellis
Philippe Malcolm
Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
PLoS Computational Biology
title Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
title_full Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
title_fullStr Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
title_full_unstemmed Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
title_short Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles.
title_sort differences between joint space and musculoskeletal estimations of metabolic rate time profiles
url https://doi.org/10.1371/journal.pcbi.1008280
work_keys_str_mv AT arashmohammadzadehgonabadi differencesbetweenjointspaceandmusculoskeletalestimationsofmetabolicratetimeprofiles
AT prokopiosantonellis differencesbetweenjointspaceandmusculoskeletalestimationsofmetabolicratetimeprofiles
AT philippemalcolm differencesbetweenjointspaceandmusculoskeletalestimationsofmetabolicratetimeprofiles