Smart self management: assistive technology to support people with chronic disease

H R Zheng, C Nugent, P McCullagh, Y Huang, S M Zhang, W Burns, R Davies, N Black, P Wright, S Mawson, Christopher Eccleston, M Hawley, G Mountain

Research output: Contribution to journalArticlepeer-review

41 Citations (SciVal)

Abstract

We have developed a personalised self management system to support self management of chronic conditions with support from health-care professionals. Accelerometers are used to measure gross levels of activity, for example walking around the house, and used to infer higher level activity states, such as standing, sitting and lying. A smart phone containing an accelerometer and a global positioning system (GPS) module can be used to monitor outdoor activity, providing both activity and location based information. Heart rate, blood pressure and weight are recorded and input to the system by the user. A decision support system (DSS) detects abnormal activity and distinguishes life style patterns. The DSS is used to assess the self management process, and automates feedback to the user, consistent with the achievement of their life goals. We have found that telecare and assistive technology is feasible to support self management for chronic conditions within the home and local community environments.
Original languageEnglish
Pages (from-to)224-227
Number of pages4
JournalJournal of Telemedicine and Telecare
Volume16
Issue number4
DOIs
Publication statusPublished - Jun 2010

Fingerprint

Dive into the research topics of 'Smart self management: assistive technology to support people with chronic disease'. Together they form a unique fingerprint.

Cite this