A Muscle Model Incorporating Fiber Architecture Features for the Estimation of Joint Stiffness During Dynamic Movement

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Quantifying human joint stiffness in vivo during movement remains challenging. Well established stiffness estimation methods include system identification and the notion of quasi-stiffness, with experimental and conceptual limitations, respectively. Joint stiffness computation via biomechanical models is an emerging solution to overcome such limitations. However, these models make assumptions that hamper their generalization across muscle architectures. Here we present a stiffness formulation that considers the muscle’s pennation angle, and its comparison to a simpler formulation that does not. Model-based stiffness estimates are evaluated against joint-perturbation-based system identification. Results on muscles with different pennation angle show that our formulation seamlessly adjusts the muscle-tendon units’ stiffness depending on their architecture. At the joint level, our new model improved the stiffness estimations. Our study’s relevance is the creation and validation of a modeling formulation that does not require joint perturbation. This will enable better estimations and understanding of stiffness properties and human movement.

Original languageEnglish
Title of host publicationConverging Clinical and Engineering Research on Neurorehabilitation IV
Subtitle of host publicationProceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13–16, 2020
EditorsDiego Torricelli, Metin Akay, Jose L. Pons
PublisherSpringer Science + Business Media
Pages507-511
Number of pages5
ISBN (Electronic)978-3-030-70316-5
ISBN (Print)978-3-030-70315-8, 978-3-030-70318-9
DOIs
Publication statusPublished - 2022
Event5th International Conference on NeuroRehabilitation, ICNR 2020 - Virtual Event
Duration: 13 Oct 202016 Oct 2020
Conference number: 5

Publication series

NameBiosystems and Biorobotics
Volume28
ISSN (Print)2195-3562
ISSN (Electronic)2195-3570

Conference

Conference5th International Conference on NeuroRehabilitation, ICNR 2020
Abbreviated titleICNR 2020
CityVirtual Event
Period13/10/2016/10/20

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