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

Christopher P. Cop*, Alfred C. Schouten, Bart F.J.M. Koopman, M. Sartori

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review

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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
ISBN (Electronic)978-3-030-70316-5
ISBN (Print)978-3-030-70315-8
Publication statusPublished - 2022
EventICNR 2020: International Conference on NeuroRehabilitation (Virtual) -
Duration: 13 Oct 202016 Oct 2020

Publication series

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


ConferenceICNR 2020: International Conference on NeuroRehabilitation (Virtual)

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


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