Date of Award
Winter 3-22-2025
Document Type
Dissertation
Degree Name
Ph.D. in Mechanical Engineering
Organizational Unit
Daniel Felix Ritchie School of Engineering and Computer Science, Mechanical and Materials Engineering
First Advisor
Kevin B. Shelburne
Second Advisor
Casey A. Myers
Third Advisor
Paul J. Rullkoetter
Copyright Statement / License for Reuse
All Rights Reserved.
Keywords
Fluoroscopy, Knee, Osetoarthritis, Robotic total knee arthroplasty (TKA)
Abstract
The human knee joint is a complex and intricate structure, enabling a wide range of motions and facilitating various dynamic activities throughout a person's lifetime. The combination of the knee's complexity and its role as a primary load-bearing joint has made it susceptible to regular wear and tear, leading to pain and the development of Osteoarthritis (OA), to which, the only treatment currently is total knee arthroplasty (TKA). Despite TKA being a mature procedure, 20% of patients receiving a TKA are dissatisfied with their “new” knee. To reduce that 20% dissatisfaction and improve surgical outcomes, orthopedic companies are developing advanced surgical robotics systems for TKA. These robots have been effective at reducing surgical procedure outliers and early reports have been favorable for patient outcomes while providing a wealth of data collected during the surgery. However, the additional data and accuracy provided by surgical robotics will be ineffective unless we can identify appropriate targets to address the pathology and underlying mechanism of OA development to restore pain free motion and quality of life to patients. Thus, this work aims to provide tools to study and investigate the mechanisms that influence knee kinematics across the 3 stages of the knee lifecycle: health, disease, and repair. These objectives were achieved through four distinct projects. The first study focused on the health stage, which aimed to collect and distribute a comprehensive high-fidelity dataset of 6 subjects (12 knees) for development of patient-specific musculoskeletal models. The second and third studies focused on the repair stage, where the use of surgical robotics were utilized to determine the surgical parameters that had the greatest influence on important postoperative measures of successful knee function across a wide range of activities of daily living. The fourth and final project focused on the disease stage, where in-vivo joint laxity and progression of OA disease were investigated for their effect on knee function prior to surgery. Overall, the goal of this dissertation is to investigate the determinants of knee motion to identify potential mechanisms of OA development and leverage high-fidelity data to inform improved targets for surgical correction and planning.
Copyright Date
3-2025
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Sean Edward Higinbotham
Provenance
Received from author
File Format
application/pdf
Language
English (eng)
Extent
220 pgs
File Size
5.4 MB
Recommended Citation
Higinbotham, Sean Edward, "Determinants of Knee Motion in Health, Disease, and Repair" (2025). Electronic Theses and Dissertations. 2529.
https://digitalcommons.du.edu/etd/2529