Elderly care: activities of daily living classification with an S band radar

Shrestha, A., Le Kernec, J. , Fioranelli, F. , Lin, Y., He, Q., Lorandel, J. and Romain, O. (2019) Elderly care: activities of daily living classification with an S band radar. Journal of Engineering, 2019(21), pp. 7601-7606. (doi: 10.1049/joe.2019.0561)

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Falls in the elderly represent a serious challenge for the global population. To address it, monitoring of daily living has been suggested, with radar emerging to be a useful platform for it due to its various benefits with acceptance and privacy. Here, we show results from the use of an S band radar for activity detection and the importance of selecting specific frequency bins to improve its suitability for human movement classification. The use of feature selection to improve detection of key activities such as falls has been presented. Initial results of 65% are improved to 85% and further to 90% with the aforementioned methods.

Item Type:Articles
Additional Information:The collaboration between University of Glasgow, University of Electronic Science and Technology of China and Université Cergy-Pontoise was partly funded by Campus France with PHC Xu Guangqi -38715QJ. A. Shrestha is supported for his PhD by the UK Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Award to the School of Engineering.
Glasgow Author(s) Enlighten ID:Fioranelli, Dr Francesco and Le Kernec, Dr Julien and Shrestha, Mr Aman
Authors: Shrestha, A., Le Kernec, J., Fioranelli, F., Lin, Y., He, Q., Lorandel, J., and Romain, O.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Journal of Engineering
Publisher:Institution of Engineering and Technology
ISSN (Online):2051-3305
Copyright Holders:Copyright © 2019 Institution of Engineering and Technology
First Published:First published in Journal of Engineering 2019(21):7601-7606
Publisher Policy:Reproduced under a Creative Commons license

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3015260Intelligent RF Sensing for Fall and Health PredictionFrancesco FioranelliEngineering and Physical Sciences Research Council (EPSRC)EP/R041679/1ENG - Systems Power & Energy