Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/93741
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dc.contributor.authorSun, Bingen
dc.contributor.authorWang, Yangen
dc.contributor.authorBanda, Jacoben
dc.date.accessioned2015-07-15T08:56:07Zen
dc.date.accessioned2019-12-06T18:44:40Z-
dc.date.available2015-07-15T08:56:07Zen
dc.date.available2019-12-06T18:44:40Z-
dc.date.copyright2014en
dc.date.issued2014en
dc.identifier.citationSun, B., Wang, Y., & Banda, J. (2014). Gait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometer. Sensors, 14(9), 17037-17054.en
dc.identifier.issn1424-8220en
dc.identifier.urihttps://hdl.handle.net/10356/93741-
dc.description.abstractGait 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.en
dc.language.isoenen
dc.relation.ispartofseriesSensorsen
dc.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 (http://creativecommons.org/licenses/by/3.0/).en
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titleGait characteristic analysis and identification based on the iPhone’s accelerometer and gyrometeren
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.identifier.doi10.3390/s140917037en
dc.description.versionPublished versionen
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item.grantfulltextopen-
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