A Human Body Gait Recognition System Based on Fourier Transform and Quartile Difference Extraction

Abstract

A research method of gait recognition based on feature combination is proposed, which includes the wavelet transform (WT), Fourier transform (FT) and the quartile difference, to explore the gait recognition system in Internet of things human body sensor based on smart phone. It can extract the low-dimensional gait parameters of the acceleration signal, and these gait parameters can reflect the movement characteristics. Then, they are combined into feature vector to identify by a pattern recognition algorithm.Finally, the experimental verification is carried out in the experimental system. The results show thatthis gait recognition method simplifies the processing flow to a certain extent, and improves the recognition accuracy. In conclusion, the algorithm has a good effect, and can identify the gait behavior with high precision.