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American Society of Biomechanics Journal of Biomechanics Award 2022: Computer models do not accurately predict human muscle passive muscle force and fiber length: Evaluating subject-specific modeling impact on musculoskeletal model predictions
Journal article   Peer reviewed

American Society of Biomechanics Journal of Biomechanics Award 2022: Computer models do not accurately predict human muscle passive muscle force and fiber length: Evaluating subject-specific modeling impact on musculoskeletal model predictions

Lomas S. Persad, Benjamin I. Binder-Markey, Alexander Y. Shin, Richard L. Lieber and Kenton R. Kaufman
Journal of biomechanics, v 159, 111798
Oct 2023
DOI: https://doi.org/10.1016/j.jbiomech.2023.111798
PMID: 37713970

Abstract

Gracilis Intraoperative OpenSim Passive muscle force Subject-specific modeling
Musculoskeletal models are valuable for studying and understanding the human body in a variety of clinical applications that include surgical planning, injury prevention, and prosthetic design. Subject-specific models have proven to be more accurate and useful compared to generic models. Nevertheless, it is important to validate all models when possible. To this end, gracilis muscle–tendon parameters were directly measured intraoperatively and used to test model predictions. The aim of this study was to evaluate the benefits and limitations of systematically incorporating subject-specific variables into muscle models used to predict passive force and fiber length. The results showed that incorporating subject-specific values generally reduced errors, although significant errors still existed. Optimization of the modeling parameter “tendon slack length” was explored in two cases: minimizing fiber length error and minimizing passive force error. The results showed that using all subject-specific values yielded the most favorable outcome in both models and optimization cases. However, the trade-off between fiber length error and passive force error will depend on the specific circumstances and research objectives due to significant individual errors. Notably, individual fiber length and passive force errors were as high as 20% and 37% respectively. Finally, the modeling parameter “tendon slack length” did not correlate with any real-world anatomical length.

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6 citations in Web of Science
4 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Biophysics
Engineering, Biomedical
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