Defense Date


Document Type


Degree Name

Master of Science


Biomedical Engineering


Musculoskeletal computational modeling is a versatile and effective tool which may be used to study joint mechanics, examine muscle and ligament function, and simulate surgical reconstructive procedures. While injury to the elbow joint can be significantly debilitating, questions still remain regarding its normal, pathologic, and repaired behavior. Biomechanical models of the elbow have been developed, but all have assumed fixed joint axes of rotation and ignored the effects of ligaments. Therefore, the objective of this thesis was to develop and validate a computational model of the elbow joint whereby joint kinematics are dictated by three-dimensional bony geometry contact, ligamentous constraints, and muscle loading.Accurate three-dimensional bone geometry was generated by acquiring CT scans, segmenting the images to isolate skeletal features, and fitting surfaces to the segmented data. Ligaments were modeled as tension-only linear springs, and muscle were represented as force vectors with discrete attachment points. Bone contact was modeled by a routine which applied a normal force at points of penetration, with a force magnitude being a function of penetration depth. A rigid body dynamics simulator was used to predict the model's behavior under particular external loading conditions.The computational model was validated by simulating past experimental investigations and comparing results. Passive flexion-extension range of motion predicted by the model correlated exceptionally well with reported values. Bony and ligamentous structures responsible for enforcing motion limits also agreed with past observations. The model's varus stability as a function of elbow flexion and coronoid process resection was also investigated. The trends predicted by the model matched those of the associated cadaver study.This thesis successfully developed an accurate musculoskeletal computational model of the elbow joint complex. While the model may now be used in a predictive manner, further refinements may expand its applicability. These include accounting for the interference between soft tissue and bone, and representing the dynamic behavior of muscles.


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Date of Submission

June 2008