Osteoarthritis (OA) is a degenerative joint disease that affects over 600 million people worldwide, with knee OA being the most common. Using OA as our focal point, our lab operates throughout the entire scope of joint health. In active individuals, we look at musculoskeletal injuries and sports biomechanics. For people diagnosed with OA, we study daily movement patterns in hopes to slow progression. And finally, for people with joint replacements, we analyze factors that might limit individual joint motion.
To understand how movement affects musculoskeletal/joint health, we need to account for all the individual factors that can affect movement (age, body size, prior injuries, etc.) and look at the multi-dimensional and time-varying patterns of movement that the body experiences in everyday life.
We utilize several different tools to capture movement during specific activities as well as patterns of physical activity during daily life, including markered and markerless motion capture, force platforms, wearable sensors (e.g., accelerometers, smart watches), and more. Computational resources, such as UF’s supercomputer, HiPerGator, and data analysis approaches such as machine learning, help us identify patterns among these different sources of information that are related to musculoskeletal/joint health outcomes.
Current Projects
- Machine Learning Model for Running Injury Prediction
- Softball Swing Analysis
- Multicenter Osteoarthritis Study
- Florida Moves (FLoMo) Study
- Pain Flares
- Shared Strides Study
- Hip motion during yoga in individuals post-total hip arthroplasty