Research on Characteristics of Human Gait by Electrostatic Detection

Abstract

Electrostatic detection is remarkably developed and has been employed to detect human activity for years. In this paper, an induction electrostatic detector is designed, and used to measure human walking signals. The gait signals of totally six segments of the same object are measured in the experiment. An algorithm is proposed to obtain accurate gait cycle. The original signals are transformed to correlation coefficient series. Peaks of correlation coefficient series is picked out as the same phase point instead of peaks of walking signal. The time between very second peaks is defined as gait cycle of object. Based on the gait cycle, we discussed the recurrence property as the characteristics of human beings. It is expected that the slope of the recurrence line can be used as an index, and will indicate the personal particularity of objects in detection and their physical conditions.