Sammanfattning

Osteoarthritis is a degenerative joint disorder, which gradually breaks down cartilage and underlying bone. The disorder is commonly present in the hip joint, where it can cause anatomical changes that may result in painful movement. Early identification of osteoarthritis may facilitate treatment for slowing the disease progression. This master’s thesis aimed to develop a pipeline for applying subject-specific boundary conditions from motion capture data on a FE model of the hip joint. The pipeline combines experimental motion capture data, musculoskeletal modelling and finite element modelling into an integrated framework. Thus, prediction of cartilage stress distributions within the hip could be computed, providing insight into subject-specific alterations in cartilage loading that are thought to contribute to the initiation and progression of osteoarthritis. Motion capture data from walking and running trials were used to extract hip kinematics and joint reaction forces for one single subject through musculoskeletal modelling. These outputs were used as inputs in the FE model to mimic subject-specific loading for simulations of the stance phase for walking and running, respectively. Results showed that the computed joint reaction forces in the musculoskeletal modelling exhibited force profiles similar to those reported in literature with magnitudes of 4 body weight (BW) for walking and 8-9 BW for running. The predicted cartilage stresses exhibited similar ranges in magnitude compared to literature for both gaits with highest magnitudes of 11 MPa for walking and 13.5 MPa for running. This pipeline provides a foundation for future studies to combine motion capture data into cartilage-level stress distributions through an integrated modelling framework. Thus, improved knowledge of stress distributions within healthy hips is enabled, which might support research for early detection and treatment of osteoarthritis.

Utforska vidare

Liknande uppsatser

Uppsatser med liknande ämnen och nyckelord.