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Inertial Motion Capture-Based Whole-Body Inverse Dynamics

Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-bod...

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Autores principales: Diraneyya, Mohsen M., Ryu, JuHyeong, Abdel-Rahman, Eihab, Haas, Carl T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587542/
https://www.ncbi.nlm.nih.gov/pubmed/34770660
http://dx.doi.org/10.3390/s21217353
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author Diraneyya, Mohsen M.
Ryu, JuHyeong
Abdel-Rahman, Eihab
Haas, Carl T.
author_facet Diraneyya, Mohsen M.
Ryu, JuHyeong
Abdel-Rahman, Eihab
Haas, Carl T.
author_sort Diraneyya, Mohsen M.
collection PubMed
description Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-body model that eliminates the usage of force plates (FPs) and uses motion patterns captured by an IMC system to predict the net forces and moments in 14 major joints. We validated the model by comparing its estimates of Ground Reaction Forces (GRFs) to the ground truth obtained from FPs and comparing predictions of the static model’s net joint moments to those predicted by 3D Static Strength Prediction Program (3DSSPP). The relative root-mean-square error (rRMSE) in the predicted GRF was 6% and the intraclass correlation of the peak values was 0.95, where both values were averaged over the subject population. The rRMSE of the differences between our model’s and 3DSSPP predictions of net L5/S1 and right and left shoulder joints moments were 9.5%, 3.3%, and 5.2%, respectively. We also compared the static and dynamic versions of the model and found that failing to account for body motions can underestimate net joint moments by 90% to 560% of the static estimates.
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spelling pubmed-85875422021-11-13 Inertial Motion Capture-Based Whole-Body Inverse Dynamics Diraneyya, Mohsen M. Ryu, JuHyeong Abdel-Rahman, Eihab Haas, Carl T. Sensors (Basel) Article Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-body model that eliminates the usage of force plates (FPs) and uses motion patterns captured by an IMC system to predict the net forces and moments in 14 major joints. We validated the model by comparing its estimates of Ground Reaction Forces (GRFs) to the ground truth obtained from FPs and comparing predictions of the static model’s net joint moments to those predicted by 3D Static Strength Prediction Program (3DSSPP). The relative root-mean-square error (rRMSE) in the predicted GRF was 6% and the intraclass correlation of the peak values was 0.95, where both values were averaged over the subject population. The rRMSE of the differences between our model’s and 3DSSPP predictions of net L5/S1 and right and left shoulder joints moments were 9.5%, 3.3%, and 5.2%, respectively. We also compared the static and dynamic versions of the model and found that failing to account for body motions can underestimate net joint moments by 90% to 560% of the static estimates. MDPI 2021-11-05 /pmc/articles/PMC8587542/ /pubmed/34770660 http://dx.doi.org/10.3390/s21217353 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Diraneyya, Mohsen M.
Ryu, JuHyeong
Abdel-Rahman, Eihab
Haas, Carl T.
Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title_full Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title_fullStr Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title_full_unstemmed Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title_short Inertial Motion Capture-Based Whole-Body Inverse Dynamics
title_sort inertial motion capture-based whole-body inverse dynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587542/
https://www.ncbi.nlm.nih.gov/pubmed/34770660
http://dx.doi.org/10.3390/s21217353
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