Lifelogging data validation model for internet of things enabled personalized healthcare

Yang, Po and Stankevicius, Dainius and Marozas, Vaidotas and Deng, Zhikun and LIu, Enjie and Lukosevicius, Arunas and Dong, Feng and Xu, Dali and Min, Geyong (2018) Lifelogging data validation model for internet of things enabled personalized healthcare. IEEE Transactions on Systems, Man and, Cybernetics: Systems, 48 (1). pp. 50-64. ISSN 2168-2216 (https://doi.org/10.1109/TSMC.2016.2586075)

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Abstract

Internet of Things (IoT) technology offers opportunities to monitor lifelogging data by a variety of assets, like wearable sensors, mobile apps, etc. But due to heterogeneity of connected devices and diverse human life patterns in an IoT environment, lifelogging personal data contains huge uncertainty and are hardly used for healthcare studies. Effective validation of lifelogging personal data for longitudinal health assessment is demanded. In this paper, lifelogging physical activity (LPA) is taken as a target to explore how to improve the validity of lifelogging data in an IoT enabled healthcare system. A rule-based adaptive LPA validation (LPAV) model, LPAV-IoT, is proposed for eliminating irregular uncertainties (IUs) and estimating data reliability in IoT healthcare environments. A methodology specifying four layers and three modules in LPAV-IoT is presented for analyzing key factors impacting validity of LPA. A series of validation rules are designed with uncertainty threshold parameters and reliability indicators and evaluated through experimental investigations. Following LPAV-IoT, a case study on a personalized healthcare platform myhealthavatar connecting three state-of-the-art wearable devices and mobile apps are carried out. The results reflect that the rules provided by LPAV-IoT enable efficiently filtering at least 75% of IU and adaptively indicating the reliability of LPA data on certain condition of IoT environments.

  • Item type:Article
    ID code:70600
    Dates:
    Date
    Event
    31 January 2018
    Published
    19 July 2016
    Published Online
    18 June 2016
    Accepted
    Notes:(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Medicine
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:21 Nov 2019 12:37
    Last modified:11 Nov 2024 12:30
    URI:https://strathprints.strath.ac.uk/id/eprint/70600
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