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

      Zhao, Youbing; Parvinzamir, Farzad; Portokallidis, Nick; Third, Allan; Drosatos, George; Wei, Hui; Deng, Zhikun; Liu, Enjie; Dong, Feng; Wilson, Stephen; et al. (Springer, 2016-10-27)
      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.
    • MyHealthAvatar and CARRE: case studies of interactive visualisation for Internet-enabled sensor-assisted health monitoring and risk analysis

      Zhao, Youbing; Parvinzamir, Farzad; Deng, Zhikun; Wei, Hui; Zhao, Xia; Liu, Enjie; Dong, Feng; Clapworthy, Gordon J.; Lukoševičius, Arūnas; Marozas, Vaidotas; et al. (IET, 2016-10-13)
      With the progress of wearable sensor technologies, more wearable health sensors have been made available on the market, which enables not only people to monitor their health and lifestyle in a continuous way but also doctors to utilise them to make better diagnoses. Continuous measurement from a variety of wearable sensors implies that a huge amount of data needs to be collected, stored, processed and presented, which cannot be achieved by traditional data processing methods. Visualisation is designed to promote knowledge discovery and utilisation via mature visual paradigms with well-designed user interactions and has become indispensable in data analysis. In this paper we introduce the role of visualisation in wearable sensor-assisted health analysis platforms by case studies of two projects funded by the European Commission: MyHealthAvatar and CARRE. The former focuses on health sensor data collection and lifestyle tracking while the latter aims to provide innovative means for the management of cardiorenal diseases with the assistance of wearable sensors. The roles of visualisation components including timeline, parallel coordinates, map, node-link diagrams, Sankey diagrams, etc. are introduced and discussed.
    • Visual analytics for health monitoring and risk management in CARRE

      Zhao, Youbing; Parvinzamir, Farzad; Wei, Hui; Liu, Enjie; Deng, Zhikun; Dong, Feng; Third, Allan; Lukoševičius, Arūnas; Marozas, Vaidotas; Kaldoudi, Eleni; et al. (Springer Verlag, 2016-12-31)
      With the rise of wearable sensor technologies, an increasing number of wearable health and medical sensors are available on the market, which enables not only people but also doctors to utilise them to monitor people’s health in such a consistent way that the sensors may become people’s lifetime companion. The consistent measurements from a variety of wearable sensors implies that a huge amount of data needs to be processed, which cannot be achieved by traditional processing methods. Visual analytics is designed to promote knowledge discovery and utilisation of big data via mature visual paradigms with well-designed user interactions and has become indispensable in big data analysis. In this paper we introduce the role of visual analytics for health monitoring and risk management in the European Commission funded project CARRE which aims to provide innovative means for the management of cardiorenal diseases with the assistance of wearable sensors. The visual analytics components of timeline and parallel coordinates 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 health.