Detecting idiopathic toe-walking gait pattern from normal gait pattern using heel accelerometry data and Support Vector Machines.

Download
Full text for this resource is not available from the Research Repository.
Export

Pendharkar, G, Lai, Daniel ORCID: 0000-0003-3459-7709 and Begg, Rezaul ORCID: 0000-0002-3195-8591 (2008) Detecting idiopathic toe-walking gait pattern from normal gait pattern using heel accelerometry data and Support Vector Machines. In: 30th Annual International Institute of Electrical and Electronics Engineers, Engineering in Medicine and Biology Society Conference (IEEE EMBS 2008) - Personalized Healthcare through Technology, 20 August 2008-24 August 2008, Vancouver.

Dimensions Badge

Altmetric Badge

Item type Conference or Workshop Item (Paper)
URI https://vuir.vu.edu.au/id/eprint/36001
DOI https://doi.org/10.1109/IEMBS.2008.4650317
Official URL https://ieeexplore.ieee.org/document/4650317/
ISBN 9781424418145
Subjects Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > FOR Classification > 1106 Human Movement and Sports Science
Historical > Faculty/School/Research Centre/Department > Centre for Ageing, Rehabilitation, Exercise & Sport Science (CARES)
Keywords pattern recognition; SVM; learning tools; machine learning; personalised healthcare; ITW; children; algorithms
Citations in Scopus 15 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login

CORE (COnnecting REpositories)