Engineering Commons^™

Human Behaviour Recognition With Segmented Inertial Data, Chao Sun, David A. Stirling, Fazel Naghdy

Professor Fazel Naghdy

The development and recent advancements of integrated inertial sensors has afforded substantive new possibilities for the acquisition and study of complex human motor skills and ultimately their imitation within robotic systems. This paper describes continuing work on kinetic models that are derived through unsupervised learning from a continuous stream of signals, including Euler angles and accelerations in three spatial dimensions, acquired from motions of a human arm. An intrinsic classification algorithm, MML (Minimum Message Length encoding) is used to segment the complex data, formulating a Gaussian Mixture Model of the dynamic modes it represents. Subsequent representation and analysis as FSM …