Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure

Yan Huang, Huiru Zheng, Chris Nugent, Paul McCullagh, Norman Black, Mark Hawley, Gail Mountain

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In this paper, we explore the feasibility of integrating data gleaned from home-based sensors and information from self reporting to support the self-management of Chronic Heart Failure. Time spent sleeping, television usage and utility usage were recorded by sensor based technology within the home environment for one participant over a 30 day period. Information in relation to a participant's daily self report was used to assist analysis in an effort to provide more meaningful and relevant feedback to the participant in relation to how they should manage their condition. The results indicate that trends which could lead to lifestyle change can be discovered. For example, whilst no particular cause of an unusual sleeping pattern event was discovered, the ability to identify such events could be important over longer periods of time. In conclusion, the findings from the study have suggested that feedback used to support self-management can be generated using both activity information and self report, and potentially benefits for the combination.

    LanguageEnglish
    Title of host publicationComputing in Cardiology 2011, CinC 2011
    Pages397-400
    Number of pages4
    Volume38
    Publication statusPublished - 1 Dec 2011
    EventComputing in Cardiology 2011, CinC 2011 - Hangzhou, China
    Duration: 18 Sep 201121 Sep 2011

    Conference

    ConferenceComputing in Cardiology 2011, CinC 2011
    CountryChina
    CityHangzhou
    Period18/09/1121/09/11

    Fingerprint

    Self Care
    Self Report
    Data mining
    Life Style
    Heart Failure
    Feedback
    Aptitude
    Television
    Sensors
    Technology

    Cite this

    Huang, Y., Zheng, H., Nugent, C., McCullagh, P., Black, N., Hawley, M., & Mountain, G. (2011). Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure. In Computing in Cardiology 2011, CinC 2011 (Vol. 38, pp. 397-400). [6164586]
    Huang, Yan ; Zheng, Huiru ; Nugent, Chris ; McCullagh, Paul ; Black, Norman ; Hawley, Mark ; Mountain, Gail. / Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure. Computing in Cardiology 2011, CinC 2011. Vol. 38 2011. pp. 397-400
    @inproceedings{93dbfaced3464542ac3251f46e2748d2,
    title = "Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure",
    abstract = "In this paper, we explore the feasibility of integrating data gleaned from home-based sensors and information from self reporting to support the self-management of Chronic Heart Failure. Time spent sleeping, television usage and utility usage were recorded by sensor based technology within the home environment for one participant over a 30 day period. Information in relation to a participant's daily self report was used to assist analysis in an effort to provide more meaningful and relevant feedback to the participant in relation to how they should manage their condition. The results indicate that trends which could lead to lifestyle change can be discovered. For example, whilst no particular cause of an unusual sleeping pattern event was discovered, the ability to identify such events could be important over longer periods of time. In conclusion, the findings from the study have suggested that feedback used to support self-management can be generated using both activity information and self report, and potentially benefits for the combination.",
    author = "Yan Huang and Huiru Zheng and Chris Nugent and Paul McCullagh and Norman Black and Mark Hawley and Gail Mountain",
    year = "2011",
    month = "12",
    day = "1",
    language = "English",
    isbn = "9781457706127",
    volume = "38",
    pages = "397--400",
    booktitle = "Computing in Cardiology 2011, CinC 2011",

    }

    Huang, Y, Zheng, H, Nugent, C, McCullagh, P, Black, N, Hawley, M & Mountain, G 2011, Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure. in Computing in Cardiology 2011, CinC 2011. vol. 38, 6164586, pp. 397-400, Computing in Cardiology 2011, CinC 2011, Hangzhou, China, 18/09/11.

    Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure. / Huang, Yan; Zheng, Huiru; Nugent, Chris; McCullagh, Paul; Black, Norman; Hawley, Mark; Mountain, Gail.

    Computing in Cardiology 2011, CinC 2011. Vol. 38 2011. p. 397-400 6164586.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    TY - GEN

    T1 - Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure

    AU - Huang, Yan

    AU - Zheng, Huiru

    AU - Nugent, Chris

    AU - McCullagh, Paul

    AU - Black, Norman

    AU - Hawley, Mark

    AU - Mountain, Gail

    PY - 2011/12/1

    Y1 - 2011/12/1

    N2 - In this paper, we explore the feasibility of integrating data gleaned from home-based sensors and information from self reporting to support the self-management of Chronic Heart Failure. Time spent sleeping, television usage and utility usage were recorded by sensor based technology within the home environment for one participant over a 30 day period. Information in relation to a participant's daily self report was used to assist analysis in an effort to provide more meaningful and relevant feedback to the participant in relation to how they should manage their condition. The results indicate that trends which could lead to lifestyle change can be discovered. For example, whilst no particular cause of an unusual sleeping pattern event was discovered, the ability to identify such events could be important over longer periods of time. In conclusion, the findings from the study have suggested that feedback used to support self-management can be generated using both activity information and self report, and potentially benefits for the combination.

    AB - In this paper, we explore the feasibility of integrating data gleaned from home-based sensors and information from self reporting to support the self-management of Chronic Heart Failure. Time spent sleeping, television usage and utility usage were recorded by sensor based technology within the home environment for one participant over a 30 day period. Information in relation to a participant's daily self report was used to assist analysis in an effort to provide more meaningful and relevant feedback to the participant in relation to how they should manage their condition. The results indicate that trends which could lead to lifestyle change can be discovered. For example, whilst no particular cause of an unusual sleeping pattern event was discovered, the ability to identify such events could be important over longer periods of time. In conclusion, the findings from the study have suggested that feedback used to support self-management can be generated using both activity information and self report, and potentially benefits for the combination.

    UR - http://www.scopus.com/inward/record.url?scp=84859961661&partnerID=8YFLogxK

    M3 - Conference contribution

    SN - 9781457706127

    VL - 38

    SP - 397

    EP - 400

    BT - Computing in Cardiology 2011, CinC 2011

    ER -

    Huang Y, Zheng H, Nugent C, McCullagh P, Black N, Hawley M et al. Knowledge discovery from lifestyle profiles to support self-management of chronic heart failure. In Computing in Cardiology 2011, CinC 2011. Vol. 38. 2011. p. 397-400. 6164586