Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer

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 acceleromet...

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Main Authors: Sun, Bing, Wang, Yang, Banda, Jacob
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/93741
http://hdl.handle.net/10220/38339
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-937412022-02-16T16:29:29Z Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer Sun, Bing Wang, Yang Banda, Jacob School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 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. Published version 2015-07-15T08:56:07Z 2019-12-06T18:44:40Z 2015-07-15T08:56:07Z 2019-12-06T18:44:40Z 2014 2014 Journal Article 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. 1424-8220 https://hdl.handle.net/10356/93741 http://hdl.handle.net/10220/38339 10.3390/s140917037 25222034 en Sensors © 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 (http://creativecommons.org/licenses/by/3.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Sun, Bing
Wang, Yang
Banda, Jacob
Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Sun, Bing
Wang, Yang
Banda, Jacob
format Article
author Sun, Bing
Wang, Yang
Banda, Jacob
author_sort Sun, Bing
title Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
title_short Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
title_full Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
title_fullStr Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
title_full_unstemmed Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer
title_sort gait characteristic analysis and identification based on the iphone’s accelerometer and gyrometer
publishDate 2015
url https://hdl.handle.net/10356/93741
http://hdl.handle.net/10220/38339
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