Simulation and Analysis of Human Walking Motion

Simulation and analysis of human walking motion has applications in surveillance and healthcare. In this paper we discuss an approach for modeling human walking motion using a mechanical model in the form of a kinematic chain consisting of rigid links and revolute joints. Our goal is to discriminate different types of walking motions using information such as joint torque and angle sequences extracted from the model. The angle sequences are initially extracted using 3D geometry. From these angle sequences we extract the torque sequences using a recursive Newton Euler inverse dynamics algorithm. Time series models and dynamic time warping of the torque and angle sequences are used to characterize and discriminate different walking patterns. A forward dynamics algorithm is also presented for synthesizing different walking sequences like limping from a normal walking torque sequence.