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Integrated visualisation of wearable sensor data and risk models for individualised health monitoring and risk assessment to promote patient empowerment

  • Youbing Zhao
    ,
  • Farzad Parvinzamir
    ,
  • Stephen Wilson
    ,
  • Hui Wei
    ,
  • Zhikun Deng
    ,
  • Nick Portokallidis
Research Output:
Contribution to journal
Article
 Peer-review

Open access

Abstract

Patient empowerment delivers health and social care services to enable people to take more control of their health care needs. With the advance of sensor technologies, it is increasingly possible to monitor people's health with dedicated wearable sensors. The consistent measurements from a variety of wearable sensors implies that a huge amount of data may be exploited to monitor and predict people's health with proven models. In the process of health data representation and analysis, visualization can be used to promote data analysis and knowledge discovery via mature visual paradigms with well-designed user interactions. In this paper we introduce the role of visualisation for individualized health monitoring and risk management in the background of the European Commission funded project which aims to provide self-management of cardiorenal diseases with the assistance of wearable sensors. The visualisation components of timeline for health monitoring and of node-link diagrams, chord diagrams and Sankey diagrams for risk analysis are presented to achieve ubiquitous and lifelong health and risk monitoring to promote people's wellbeing. It allows the patients not only to view existing risks but also to know the ways to change their lifestyles to reduce the risks. In addition it also allows people to selectively view and explore the risk paths in interest.

Publication Information

Output type

Research Output:
Contribution to journal
Article
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 405-413

Journal (Volume, Issue Number)

Journal of Visualization (Volume 20, Issue 2)

Publication milestones

  • Published - 27/10/2016

Publication status

Published - 27/10/2016

ISSN

1343-8875

Publication IDs

  • handle.net: 10547/623064
  • Scopus: 84992712434

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