Development of an intelligent real-time heuristic-based algorithm to identify human gait events

Human gait events are crucial in gait analysis. Proper identification of gait events enables derivation of various spatio-temporal parameters and segmentation of the data captured by motion capture systems. Rapid growth of miniature motion sensors, such as gyroscope, has allowed human motion to be captured continuously in real-time and in natural environment. This paper utilizes gyroscopes to monitor human gait and heuristic-based algorithm to define initial contact (IC) and end contact (EC) of the foot on the ground during walking. Experimental study was conducted to examine the overall performance of the proposed method. To simulate abnormal gait, knee brace and ankle brace were used to restrict knee and ankle movements during walking. This study showed that the heuristic-based algorithm can continuously define IC and EC accurately in normal and abnormal gaits.