Spatiotemporal and kinetic gait analysis system based on multisensor fusion of laser range sensor and instrumented insoles

Tracking of human legs during walking are key technologies for gait analysis evaluating the movement function of the elderly and patients with gait disorders. Although the motion capture cameras are the gold standard method for gait analysis because of their high accuracy, they are not always accessible in clinical sites because of their cost, scale, and usability. In response, a laser range sensor (LRS), which is used for obstacle avoidance and human detection of mobile robots, has recently been employed for tracking of leg motions. Some previous studies set LRS at shin height and tracked leg motions during walking using three or five observation patterns and the Kalman filtering and data association methods. However, these systems had difficulty in tracking during walking along a circular trajectory including frequent overlaps and occlusions of legs. Therefore, this paper presents a spatiotemporal and kinetic gait analysis system using a single LRS and instrumented insoles and proposes a multisensor fusion algorithm for tracking leg motions. The instrumented insoles are in-shoe devices embedded force sensors and can detect accurate timings of gait events via force sensing. The system identifies gait phases by the fusion algorithm and switches acceleration input added to motion models of tracked legs for the Kalman filter and data association. The tracking performance of the proposed system was evaluated by measuring walking on a circular trajectory in experiments.