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
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
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