Radar sensing for healthcare

Fioranelli, F. , Shah, S. A. , Li, H., Shrestha, A., Yang, S. and Le Kernec, J. (2019) Radar sensing for healthcare. Electronics Letters, 55(19), pp. 1022-1024. (doi:10.1049/el.2019.2378)

Fioranelli, F. , Shah, S. A. , Li, H., Shrestha, A., Yang, S. and Le Kernec, J. (2019) Radar sensing for healthcare. Electronics Letters, 55(19), pp. 1022-1024. (doi:10.1049/el.2019.2378)

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Abstract

Although traditionally associated with defence and security domains, radar sensing has attracted significant interest in recent years in healthcare applications. These include the monitoring of vital signs such as respiration, heartbeat, and blood pressure, analysis of gait and mobility levels, classification of human activities to promptly detect critical events such as falls, as well as the evaluation of fitness and reactivity levels. The attractiveness of radar against alternative technologies such as wearable sensors or cameras lies in its contactless capabilities, whereby people do not need to wear, carry, or interact with any additional device, and plain images of people and private environments are not recorded. In this letter, we discuss some of the most recent achievements and outstanding research challenges related to radar applications in healthcare and present some results from our work at the University of Glasgow, including a dataset of radar signatures of human activities that are openly shared with the wider community.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Li, Mr Haobo and Yang, Dr Shufan and Fioranelli, Dr Francesco and Shrestha, Mr Aman and Le Kernec, Dr Julien and Shah, Mr Syed
Authors: Fioranelli, F., Shah, S. A., Li, H., Shrestha, A., Yang, S., and Le Kernec, J.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Electronics Letters
Publisher:Institution of Engineering and Technology
ISSN:0013-5194
ISSN (Online):1350-911X
Published Online:05 August 2019
Copyright Holders:Copyright © 2019 The Institution of Engineering and Technology
First Published:First published in Electronics Letters 55(19): 1022-1024
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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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