ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Biomechanics
Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1547373
Personalization of Closed-Chain Shoulder Models Yields High Kinematic Accuracy for Multiple Motions
Provisionally accepted- 1Rice University, Houston, Texas, United States
- 2The University of Utah, Salt Lake City, Utah, United States
- 3Rush University Medical Center, Chicago, United States
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The shoulder joint complex is prone to musculoskeletal issues, such as rotator cuff-related pain, which affect two-thirds of adults and often result in suboptimal treatment outcomes. Current musculoskeletal models used to understand shoulder biomechanics are limited by challenges in personalization, inaccuracies in predicting joint and muscle loads, and an inability to simulate anatomically accurate motions. To address these deficiencies, we developed a novel, personalized modeling framework capable of calibrating subject-specific joint centers and functional axes for the shoulder complex. Leveraging in vivo biplane fluoroscopy data and the recent Joint Model Personalization Tool from the Neuromusculoskeletal Modeling Pipeline, we optimized joint parameters and body scale factors for shoulder models with varying degrees of freedom (DOFs). We initially created and tested open-chain scapula-only models (3DOF, 4DOF, and 5DOF) and found that increasing DOFs improved accuracy, with the 5 DOF model yielding the lowest marker distance errors (average = 0.8 mm, maximum = 5.2 mm) as compared to biplane fluorscopy data of the scapula across eight movement trials. We subsequently created closed-chain shoulder models incorporating scapula, clavicle, and humerus bodies. We found closed-chain shoulder models with 5 DOFs for the scapula achieved the highest accuracy (average = 0.9 mm, maximum = 5.7 mm) and showed consistent performance across subjects (n=3) in leave-one-out cross-validation tests (average marker distance errors = 1.0-1.4 mm). This framework minimizes errors in joint kinematics and provides a foundation for future models incorporating personalized musculature and advanced simulations.
Keywords: Shoulder Joint, Musculoskeletal Model, scapulothoracic kinematics, Model personalization, optimization
Received: 18 Dec 2024; Accepted: 31 Jul 2025.
Copyright: © 2025 Hammond, Henninger, Fregly and Gustafson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jonathan A Gustafson, Rush University Medical Center, Chicago, United States
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