Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.
deep learning
locomotion
machine learning
musculoskeletal modelling
running biomechanics
walking biomechanics
Journal
Frontiers in bioengineering and biotechnology
ISSN: 2296-4185
Titre abrégé: Front Bioeng Biotechnol
Pays: Switzerland
ID NLM: 101632513
Informations de publication
Date de publication:
2023
2023
Historique:
received:
19
04
2023
accepted:
25
06
2023
medline:
19
7
2023
pubmed:
19
7
2023
entrez:
19
7
2023
Statut:
epublish
Résumé
Alterations in joint contact forces (JCFs) are thought to be important mechanisms for the onset and progression of many musculoskeletal and orthopaedic pain disorders. Computational approaches to JCFs assessment represent the only non-invasive means of estimating
Identifiants
pubmed: 37465692
doi: 10.3389/fbioe.2023.1208711
pii: 1208711
pmc: PMC10350628
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1208711Informations de copyright
Copyright © 2023 Liew, Rügamer, Mei, Altai, Zhu, Zhai and Cortes.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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