Lifelogging data validation model for Internet of Things enabled healthcare system
Authors
Yang, PoStankevicius, Dainius
Marozas, Vaidotas
Deng, Zhikun
Liu, Enjie
Lukoševicǐus, Arunas
Dong, Feng
Xu, Lida
Min, Geyong
Affiliation
Liverpool John Moores UniversityKaunas University of Technology, Lithuania
Old Dominion University
University of Bedfordshire
Exeter University
Issue Date
2016-07-19Subjects
Internet of Thingsmedical services
uncertainty
biomedical monitoring
adaptation models
reliability
data models
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Show full item recordAbstract
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.Citation
Yang P, Stankevicius D, Marozas V, Deng Z, Liu E, Lukoševicǐus A, Dong F, Xu L,Min G (2016) 'Lifelogging data validation model for Internet of Things enabled healthcare system', IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48 (1), pp.50-64.Publisher
IEEEAdditional Links
http://ieeexplore.ieee.org/document/7516690/Type
ArticleLanguage
enISSN
2168-2216Sponsors
CARRE, iManageCancerae974a485f413a2113503eed53cd6c53
10.1109/TSMC.2016.2586075
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- Creative Commons
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/