User activity pattern analysis in Telecare Data

ANGELOVA, Maia, ELLMAN, Jeremy, GIBSON, Helen, OMAN, Paul, RAJASEGARAR, Sutharshan and ZHU, Ye (2018). User activity pattern analysis in Telecare Data. IEEE Access, 6 (1), 33306-33317.

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Official URL: https://ieeexplore.ieee.org/document/8385090/
Link to published version:: https://doi.org/10.1109/ACCESS.2018.2847294
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    Abstract

    Telecare is the use of devices installed in homes to deliver health and social care to the elderly and infirm. The aim of this paper is to identify patterns of use for different devices and associations between them. The data were provided by a telecare call centre in the North East of England. Using statistical analysis and machine learning, we analysed the relationships between users’ characteristics and device activations. We applied association rules and decision trees for the event analysis and our targeted projection pursuit technique was used for the user-event modelling. This study reveals that there is a strong association between users’ ages and activations, i.e., different age group users exhibit different activation patterns. In addition, a focused analysis on the users with mental health issues reveals that the older users with memory problems who live alone are likely to make more mistakes in using the devices than others. The patterns in the data can enable the telecare call centre to gain insight into their operations, and improve their effectiveness in several ways. This study also contributes to automatic analysis and support for decision making in the telecare industry.

    Item Type: Article
    Uncontrolled Keywords: Decision trees;Machine learning;Monitoring;Pattern analysis;Statistical analysis;Temperature sensors;Ageing Care;Data Analytics;Machine Learning;Statistical Analysis;Telecare
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Identification Number: https://doi.org/10.1109/ACCESS.2018.2847294
    Page Range: 33306-33317
    Depositing User: Helen Gibson
    Date Deposited: 18 Jun 2018 10:23
    Last Modified: 01 Jul 2019 14:30
    URI: http://shura.shu.ac.uk/id/eprint/21595

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