Title
Subject Specific Computational Models of the Knee to Predict Anterior Cruciate Ligament Injury
Date of Award
2009
Degree Type
Dissertation
Department
Chemical and Biomedical Engineering
First Advisor
van den Bogert, Antonie J.
Subject Headings
Knee -- Models, Knee -- Wounds and injuries, Anterior cruciate ligament -- Wounds and injuries, Knee joint model, ACL, Biomechanics, Large scale optimization, ACL injury, Knee biomechanics
Abstract
Knee joint is a complex joint involving multiple interactions between cartilage, bone, muscles, ligaments, tendons and neural control. Anterior Cruciate Ligament (ACL) is one ligament in the knee joint that frequently gets injured during various sports or recreational activities. ACL injuries are common in college level and professional athletes especially in females and the injury rate is growing in epidemic proportions despite significant increase in the research focusing on neuromuscular and proprioceptive training programs. Most ACL injuries lead to surgical reconstruction followed by a lengthy rehabilitation program impacting the health and performance of the athlete. Furthermore, the athlete is still at the risk of early onset of osteoarthritis. Regardless of the gender disparity in the ACL injury rates, a clear understanding of the underlying injury mechanisms is required in order to reduce the incidence of these injuries. Computational modeling is a resourceful and cost effective tool to investigate the biomechanics of the knee. The aim of this study was twofold. The first aim was to develop subject specific computational models of the knee joint and the second aim to gain an improved understanding of the ACL injury mechanisms using the subject specific models. We used a quasi-static, multi-body modeling approach and developed MRI based tibio-femoral computational knee joint models. Experimental joint laxity and combined loading data was obtained using five cadaveric knee specimens and a state-of-the-art robotic system. Ligament zero strain lengths and insertion points were optimized using joint laxity data. Combined loading and ACL strain data were used for model validations. ACL injury simulations were performed using factorial design approach comprising of multiple factors and levels to replicate a large and rich set of loading states. This thesis is an extensive work covering all the details of the ACL injury project explained above and highlighting the importance of 1) computational modeling in inju
Recommended Citation
Borotikar, Bhushan S., "Subject Specific Computational Models of the Knee to Predict Anterior Cruciate Ligament Injury" (2009). ETD Archive. 37.
https://engagedscholarship.csuohio.edu/etdarchive/37