Please use this identifier to cite or link to this item:
Title: Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
Authors: Sun, Bing
Wang, Yang
Banda, Jacob
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2014
Source: Sun, B., Wang, Y., & Banda, J. (2014). Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer. Sensors, 14(9), 17037-17054.
Series/Report no.: Sensors
Abstract: Gait identification is a valuable approach to identify humans at a distance. In this paper, 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 collected by the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the data sets are processed to extract gait characteristic parameters which include gait frequency, symmetry coefficient, dynamic range and similarity coefficient of characteristic curves. Finally, a weighted voting scheme dependent upon the gait characteristic parameters is proposed for gait identification. Four experiments are implemented to validate the proposed scheme. The attitude and acceleration solutions are verified by simulation. Then the gait characteristics are analyzed by comparing two sets of actual data, and the performance of the weighted voting identification scheme is verified by 40 datasets of 10 subjects.
ISSN: 1424-8220
DOI: 10.3390/s140917037
Rights: © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.