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Scapulothoracic rhythm affects glenohumeral joint force.
JSES Open Access 2019 July
Hypothesis: Musculoskeletal computer models provide valuable insights into shoulder biomechanics. The shoulder is a complex joint composed of glenohumeral, scapulothoracic, acromioclavicular, and sternoclavicular articulations, whose function is largely dependent on the many muscles spanning these joints. However, the range of patient-to-patient variability in shoulder function is largely unknown. We therefore assessed the sensitivity of glenohumeral forces to population-based model input parameters that were likely to influence shoulder function.
Methods: We constructed musculoskeletal models of the shoulder in the AnyBody Modeling System (AnyBody Technology, Aalborg, Denmark). We used inverse dynamics and static optimization to solve for glenohumeral joint forces during a simulated shoulder elevation. We generated 1000 AnyBody models by uniformly distributing the following input parameters: subject height, scapulohumeral rhythm, humeral head radius, and acromiohumeral interval.
Results: Increasing body height increased glenohumeral joint forces. Increasing the ratio of scapulothoracic to glenohumeral elevation also increased forces. Increasing humeral head radius and acromiohumeral interval decreased forces. The relative sensitivity of glenohumeral joint forces to input parameters was dependent on the angle of shoulder elevation. We developed an efficient method of generating and simulating musculoskeletal models representing a large population of shoulder arthroplasty patients. We found that scapulohumeral rhythm had a significant influence on glenohumeral joint force.
Conclusions: This finding underscores the importance of more accurately measuring and simulating scapulothoracic motion rather than using fixed ratios or average scapulothoracic motion. This modeling approach can be used to generate virtual populations for conducting efficient simulations and generating statistical conclusions.
Methods: We constructed musculoskeletal models of the shoulder in the AnyBody Modeling System (AnyBody Technology, Aalborg, Denmark). We used inverse dynamics and static optimization to solve for glenohumeral joint forces during a simulated shoulder elevation. We generated 1000 AnyBody models by uniformly distributing the following input parameters: subject height, scapulohumeral rhythm, humeral head radius, and acromiohumeral interval.
Results: Increasing body height increased glenohumeral joint forces. Increasing the ratio of scapulothoracic to glenohumeral elevation also increased forces. Increasing humeral head radius and acromiohumeral interval decreased forces. The relative sensitivity of glenohumeral joint forces to input parameters was dependent on the angle of shoulder elevation. We developed an efficient method of generating and simulating musculoskeletal models representing a large population of shoulder arthroplasty patients. We found that scapulohumeral rhythm had a significant influence on glenohumeral joint force.
Conclusions: This finding underscores the importance of more accurately measuring and simulating scapulothoracic motion rather than using fixed ratios or average scapulothoracic motion. This modeling approach can be used to generate virtual populations for conducting efficient simulations and generating statistical conclusions.
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