Dylan Kobsar
Assistant Professor, Kinesiology

My research is aimed at making biomechanics and human movement analyses more accessible and real-world relevant. Specifically, this work focuses on the use of wearable inertial sensors to help track and treat musculoskeletal disorders or injuries. When we think of wearable sensors, we often think of fitness tracking watches, but in fact wearable sensors have the capabilities to collect a variety of detailed human movement data similar to conventional motion capture gait laboratories. Further, when we combine these devices with innovative analyses (e.g., machine learning algorithms) and visualization techniques, a whole new world of possibilities for assessing human movement is realized. To this point, my research has used these accessible devices and innovative techniques to uncover patterns in human movement that can help us better understand the progression and treatment of individuals with knee osteoarthritis and running injuries.