Elastic shape analysis of human movement data

Music City Center 

Osteoarthritis (OA) is a prevalent degenerative joint disease, with the knee being the most commonly affected joint. Modern studies of knee joint injury and OA often measure biomechanical variables, particularly forces exerted during walking. However, the relationship among gait patterns, clinical profiles, and OA disease remains poorly understood. These biomechanical forces are typically represented as curves over time, but until recently, studies have relied on discrete values (or landmarks) to summarize these curves. This work aims to demonstrate an approach for analyzing full movement curves that capture key features of the gait cycle. Using data from the Intensive Diet and Exercise for Arthritis (IDEA) study, we developed a shape-based representation of variation in the full biomechanical curves and leveraged data integration methods to understand the shared variation in movement curves patterns with clinical traits. This talk will cover details of the nonparametric methods used in our approach and summarize key clinical discoveries.