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Support vector machines for young and older gait classification using inertial sensor kinematics at minimum toe clearance

Santhiranayagam, Braveena K, Lai, Daniel ORCID: 0000-0003-3459-7709 and Begg, Rezaul ORCID: 0000-0002-3195-8591 (2015) Support vector machines for young and older gait classification using inertial sensor kinematics at minimum toe clearance. EAI Endorsed Transactions on Pervasive Health and Technology, 16 (7). 173 - 178. ISSN 2411-7145

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Abstract

Paper originally presented at: 10th EAI International Conference on Body Area Networks (BODYNETS 2015) Sydney, Australia, 28-30 Sept, 2015

Item Type: Article
Uncontrolled Keywords: inertial sensor signals; risk of falling
Subjects: FOR Classification > 1106 Human Movement and Sports Science
Faculty/School/Research Centre/Department > College of Science and Engineering
Faculty/School/Research Centre/Department > Institute of Sport, Exercise and Active Living (ISEAL)
Faculty/School/Research Centre/Department > College of Sports and Exercise Science
Depositing User: Symplectic Elements
Date Deposited: 17 Sep 2018 01:55
Last Modified: 31 Jul 2019 06:14
URI: http://vuir.vu.edu.au/id/eprint/37066
DOI: https://doi.org/10.4108/eai.28-9-2015.2261579
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Citations in Scopus: 0 - View on Scopus

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