AI-Powered Human Movement Analysis. 3 credits, 3 contact hours

Catalog description

This course focuses on understanding quantitative human movement analysis using a range of methods, from experimental methods to artificial intelligence (AI) model-based methods. Over the past several decades, there has been significant advancement in our understanding of human movement. In the field of rehabilitation, a deeper understanding of human movement, particularly in individuals with neurologic disorders, neuromuscular diseases, and musculoskeletal injuries, can provide insights into the mechanisms underlying abnormal movements and potential treatment strategies. However, it has been acknowledged that the findings from controlled laboratory settings may not generalize to real-world movement patterns. Along with the recent advancements in AI and sensor technologies, various feasible tools have been introduced for quantifying human movement in a more practical manner. This course will cover the fundamentals of human kinematics and kinetics, the concept of recurrent/convolutional neural networks, and hands-on experience with a microcontroller, inertial measurement unit, MATLAB programming, and currently available open-source algorithms.