Human gait estimation using a reduced number of accelerometers

This study attempts to use two on-off switch sensors on feet and three tri-axis accelerometers, two in thigh and one in waist, to measure the hip angles and estimate the knee angles for a complete human gait signal acquisition. The human gait parameters like cadence, step length and walking speed are computed based on these information. For reduction of sensors for practical purpose, we focus on dynamic human gait estimation rather than stationary position. A simple dynamic model for legs is applied with two switch sensors to estimate knee angles. Stereo vision is used as a ground reference and parameters calibration for system model. A user interface for data analysis and monitoring is built to see the information such as the angle range of hip and the symmetry of two legs. We also apply a 3D virtual human model to present a real-time display of the human gait.