Date of Thesis
Summer 2026
Description
Anterior knee pain affects approximately 25% of adults and is associated with altered joint mechanics. Patellofemoral joint (PFJ) models vary widely in complexity, with no established gold standard. Musculoskeletal models efficiently estimate joint loading but do not capture tissue-level mechanics, whereas finite element (FE) models provide tissue-level predictions at greater computational cost. This thesis developed a workflow to evaluate relationships between musculoskeletal model-predicted PFJ loads and FE-predicted cartilage mechanics, examined the impact of altered quadriceps activation, and introduced improved computational models.
Marker trajectories and ground reaction forces were collected from four adults (2 male, 2 female) during walking and squatting. Musculoskeletal optimal control was used to estimate kinematics, quadriceps activations, and PFJ reaction forces (PFJRF). An Abaqus FE model based on OpenKnee geometry was used to evaluate patellar cartilage mechanics. Linear regression assessed relationships between PFJRF and cartilage outcomes. Altered activations were simulated using MocoInverse, and OpenKnee experimental data were used for model validation.
Greater PFJRF was strongly associated with increased patellar cartilage von Mises stress, hydrostatic pressure, and contact area in a healthy-subject simulation (R² = 0.98, 0.99, and 0.87, respectively). Dominant vastus lateralis activation without sufficient medial quadriceps support produced lateral patellar shift, reduced contact area, and increased cartilage stress.
Rigorously validated musculoskeletal models can infer changes in PFJ cartilage mechanics while requiring substantially less computational effort than FE models. When validated for specific activities, these models may support clinical assessment of activity-related PFJ loading and help identify conditions that increase cartilage overload and anterior knee pain risk.
Keywords
Anterior knee pain, Joint reaction force, Patellar cartilage, Finite Element Analysis, Musculoskeletal Modeling, Motion capture
Access Type
Masters Thesis
Degree Type
Master of Science in Mechanical Engineering
Major
Mechanical Engineering
First Advisor
Benjamin Wheatley
Recommended Citation
Rashedi, Mahmood, "The Development and Implementation of a Computational Framework to Simulate Patellofemoral Joint Mechanics" (2026). Master’s Theses. 319.
https://digitalcommons.bucknell.edu/masters_theses/319
Included in
Biomechanical Engineering Commons, Musculoskeletal System Commons, Other Biomedical Engineering and Bioengineering Commons, Tissues Commons