Gait Characteristic Analysis and Identification Based on the iPhone’s Accelerometer and Gyrometer

Abstract

Gait identification is a valuable approach to identify humans at a distance. In thispaper, gait characteristics are analyzed based on an iPhone’s accelerometer and gyrometer,and a new approach is proposed for gait identification. Specifically, gait datasets are collectedby the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the datasets areprocessed to extract gait characteristic parameters which include gait frequency, symmetrycoefficient, dynamic range and similarity coefficient of characteristic curves. Finally, aweighted voting scheme dependent upon the gait characteristic parameters is proposed forgait identification. Four experiments are implemented to validate the proposed scheme. Theattitude and acceleration solutions are verified by simulation. Then the gait characteristicsare analyzed by comparing two sets of actual data, and the performance of the weightedvoting identification scheme is verified by 40 datasets of 10 subjects.

Keywords

• gait
• iPhone
• accelerometer
• identification
• weighted voting