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Sensor-based Vital Sign Monitoring, Analysis and Visualisation for Ageing in Place

Kerr, Emmett, Coleman, SA, Kerr, Dermot, Vance, Philip, Gardiner, Bryan, McGinnity, TM, Zhang, Yunzhou, Fei, Wang and Wu, Chengdong (2018) Sensor-based Vital Sign Monitoring, Analysis and Visualisation for Ageing in Place. In: 2018 IEEE World Congress on Computational Intelligence (WCCI 2018), Rio de Janeiro, Brazil.. IEEE. 7 pp. [Conference contribution]

[img] Text - Accepted Version
[img] Text - Supplemental Material


With the ever-increasing global population and average life expectancy, care homes and care at home services are continuously being stretched beyond capacity. Recent developments in tactile sensing have enabled robot systems to measure human vital signs such as beats per minute (BPM), Respiratory Rate (RR) and Capillary Refill Time (CRT). Using robotic systems to measure vital sign data in the home of an elderly or disabled person would greatly assist medical and health services. This paper proposes the use of a vital sign measuring robotic system together with Cloud computing to intelligently process big data and ascertain the current health status of the service user without the need to expose their identity or burden health professionals. Furthermore, a method that enables medical professionals to visualise the data for a complete geographical region as well as for individual patients is presented and hence we provide details of a closed loop system to support ageing-in-place.

Item Type:Conference contribution (Paper)
Keywords:tactile sensing, cloud computing, data visualisation, health status
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:39945
Deposited By: Mr Emmett Kerr
Deposited On:24 Apr 2018 15:30
Last Modified:24 Apr 2018 15:30

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