Motion coaching systems for pervasive health

Abstract

Our goal is to develop a system for coaching human motions (e.g., for rehabilitation and daily health maintenance). This paper focuses on how to coach a user so that his/her motion gets closer to the good template of a target motion. It is important to efficiently advise the user to emulate the crucial features that define the good template. The proposed system (1) automatically mines the crucial features of any kind of motion from a set of motion features and (2) gives the user feedback about how to modify the motion through an intuitive interface. The crucial features are mined by feature sparsification through binary classification between the samples of good and other motions. An interface for motion coaching is designed to give feedback via different channels (e.g., visually, aurally), depending on the type of error. To use the total system, all the user must do is just move and then get feedback on the motion. Following experimental results, open problems for future work are discussed.