Work

A detailed musculoskeletal multibody simulation framework for computational analysis of the glenohumeral joint biomechanics after total shoulder replacement

Year: 2026

Type: article

Abstract: To achieve optimal stability and mobility after total shoulder replacement, a comprehensive understanding of post-operative glenohumeral biomechanics is required, which cannot be easily obtained directly from in vivo measurements. Therefore, we developed a musculoskeletal multibody simulation framework of the upper extremity after anatomical total shoulder replacement that combines a six-degree-of-freedom glenohumeral joint, detailed muscle representations, a frictional contact model between implant components, and a computed muscle control algorithm. The framework integrates inverse and forward dynamics to track predefined kinematics, while solving the muscle distribution problem through static optimization. Using this framework, outcome measures such as muscle forces, joint contact forces, contact pressure and area, center of pressure trajectory, and humeral head translations were estimated for one subject performing a 120° thoracohumeral arm elevation in the scapular plane. The reliability of the presented simulation framework was assessed by tracking prescribed kinematics and by indirect validation of the findings against previously reported data from experimental and in vivo instrumented implant measurements, and similar simulation studies. The computed muscle control algorithm accurately reproduced the desired joint trajectories, with a tracking error of less than 0.2°, and demonstrated high computational performance. Estimated glenohumeral joint quantities generally fell within the ranges reported in literature and reproduced features such as posterior-superior loading on the glenoid and small translations consistent with concavity-compression stabilization. The results suggest that the presented framework can provide realistic estimates of glenohumeral biomechanics after total shoulder replacement and may serve as a basis for future work on patient-specific analysis of implant design, positioning, and soft-tissue conditions.

Source: Computers in Biology and Medicine

DOI: 10.1016/j.compbiomed.2026.111557