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Predictive simulations of neuromuscular coordination and joint-contact loading in human gait
Lin, Yi-Chung Walter, Jonathan P. Pandy, Marcus G.
Lin, Yi-Chung
Walter, Jonathan P.
Pandy, Marcus G.
Abstract
We implemented direct collocation on a full-body neuromusculoskeletal model to calculate muscle forces, ground reaction forces and knee contact loading simultaneously for one cycle of human gait. A data-tracking collocation problem was solved for walking at the normal speed to establish the practicality of incorporating a 3D model of articular contact and a model of foot–ground interaction explicitly in a dynamic optimization simulation. The data-tracking solution then was used as an initial guess to solve predictive collocation problems, where novel patterns of movement were generated for walking at slow and fast speeds, independent of experimental data. The data-tracking solutions accurately reproduced joint motion, ground forces and knee contact loads measured for two total knee arthroplasty patients walking at their preferred speeds. RMS errors in joint kinematics were < 2.0° for rotations and < 0.3 cm for translations while errors in the model-computed ground-reaction and knee-contact forces were < 0.07 BW and < 0.4 BW, respectively. The predictive solutions were also consistent with joint kinematics, ground forces, knee contact loads and muscle activation patterns measured for slow and fast walking. The results demonstrate the feasibility of performing computationally-efficient, predictive, dynamic optimization simulations of movement using full-body, muscle-actuated models with realistic representations of joint function.
Keywords
musculoskeletal model, dynamic optimization, collocation, knee contact model, foot–ground interaction
Date
2018
Type
Journal article
Journal
Annals of Biomedical Engineering
Book
Volume
46
Issue
8
Page Range
1216-1227
Article Number
ACU Department
School of Behavioural and Health Sciences
Faculty of Health Sciences
Faculty of Health Sciences
Relation URI
Source URL
Event URL
Open Access Status
Published as green open access
License
File Access
Open
Controlled
Controlled