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

Emmett Kerr, SA Coleman, Dermot Kerr, Philip Vance, Bryan Gardiner, TM McGinnity, Yunzhou Zhang, Wang Fei, Chengdong Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

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.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Number of pages7
Publication statusAccepted/In press - 14 Mar 2018
Event2018 IEEE World Congress on Computational Intelligence (WCCI 2018) - Rio de Janeiro, Brazil.
Duration: 14 Mar 2018 → …

Conference

Conference2018 IEEE World Congress on Computational Intelligence (WCCI 2018)
Period14/03/18 → …

Keywords

  • tactile sensing
  • cloud computing
  • data visualisation
  • health status

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