Abstract

Info

Author(s):: WANG Haolun1; ZHU Ye’an1; XUWeiyi1; XU Ran1; HUANG Yuegu1; LUWei2; 1. College of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China; 2. Department of Rehabilitation Medicine, Jiangxi Provincial People’s Hospital, Nanchang 330006, China

Keywords:: Keywords: gait disorder; gait recognition; depth camera; information gain; feature ranking

Abstract:: Abstract: Agait recognition method based on skeleton keypoint detection technology is proposed, and the importance of common gait features in the diagnosis of gait disorders is discussed, so as to provide a reference for the timely examination and recognition of gait disorders. Firstly, an experimental group and two control groups are set up according to different gait patterns. All the subjects complete the prescribed normal motions according to the requirements, and the real-time movement trajectory data of skeleton keypoints of the subjects are obtained via depth camera. Then, gait recognition features are extracted from the obtained data. Finally, the importance of gait recognition features is ordered by fuzzy binary comparison decision method based on information gain, thereby providing a reference for the diagnosis and automatic recognition of gait disorders. Significant differences are found in all features for gait recognition among 3 different gait patterns. The priority order of gait features is as follows: stride frequency, maximum flextion angle of knee, toe-out angle, maximum flextion angle of hip, stride, stance phase, gait speed, maximum extension angle of hip, L/R distance of the center of mass, maximum extenstion angle of knee, U/D distance of the center of mass, step length and stride width.