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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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 |
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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 |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Sun, Bing Wang, Yang Banda, Jacob |
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Article |
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Sun, Bing Wang, Yang Banda, Jacob |
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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 |
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2015 |
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https://hdl.handle.net/10356/93741 http://hdl.handle.net/10220/38339 |
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