An Optimization Method Tracking EMG, Ground Reactions Forces, and Marker Trajectories for Musculo-Tendon Forces Estimation in Equinus Gait.

co-contraction direct multiple shooting musculo-tendon forces musculoskeletal modeling neuromusculoskeletal simulations

Journal

Frontiers in neurorobotics
ISSN: 1662-5218
Titre abrégé: Front Neurorobot
Pays: Switzerland
ID NLM: 101477958

Informations de publication

Date de publication:
2019
Historique:
received: 26 03 2019
accepted: 24 06 2019
entrez: 6 8 2019
pubmed: 6 8 2019
medline: 6 8 2019
Statut: epublish

Résumé

In the context of neuro-orthopedic pathologies affecting walking and thus patients' quality of life, understanding the mechanisms of gait deviations and identifying the causal motor impairments is of primary importance. Beside other approaches, neuromusculoskeletal simulations may be used to provide insight into this matter. To the best of our knowledge, no computational framework exists in the literature that allows for predictive simulations featuring muscle co-contractions, and the introduction of various types of perturbations during both healthy and pathological gait types. The aim of this preliminary study was to adapt a recently proposed EMG-marker tracking optimization process to a lower limb musculoskeletal model during equinus gait, a multiphase problem with contact forces. The resulting optimization method tracking EMG, ground reactions forces, and marker trajectories allowed an accurate reproduction of joint kinematics (average error of 5.4 ± 3.3 mm for pelvis translations, and 1.9 ± 1.3° for pelvis rotation and joint angles) and ensured good temporal agreement in muscle activity (the concordance between estimated and measured excitations was 76.8 ± 5.3 %) in a relatively fast process (3.88 ± 1.04 h). We have also highlighted that the tracking of ground reaction forces was possible and accurate (average error of 17.3 ± 5.5 N), even without the use of a complex foot-ground contact model.

Identifiants

pubmed: 31379547
doi: 10.3389/fnbot.2019.00048
pmc: PMC6646662
doi:

Banques de données

figshare
['10.6084/m9.figshare.7869293']

Types de publication

Journal Article

Langues

eng

Pagination

48

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Auteurs

Florent Moissenet (F)

Centre National de Rééducation Fonctionnelle et de Réadaptation-Rehazenter, Luxembourg, Luxembourg.

Colombe Bélaise (C)

Laboratory of Simulation and Movement Modeling, School of Kinesiology and Exercise Sciences, Université de Montréal, Montreal, QC, Canada.

Elodie Piche (E)

Laboratory of Simulation and Movement Modeling, School of Kinesiology and Exercise Sciences, Université de Montréal, Montreal, QC, Canada.

Benjamin Michaud (B)

Laboratory of Simulation and Movement Modeling, School of Kinesiology and Exercise Sciences, Université de Montréal, Montreal, QC, Canada.
Sainte-Justine Hospital Research Center, Montreal, QC, Canada.

Mickaël Begon (M)

Laboratory of Simulation and Movement Modeling, School of Kinesiology and Exercise Sciences, Université de Montréal, Montreal, QC, Canada.
Sainte-Justine Hospital Research Center, Montreal, QC, Canada.

Classifications MeSH