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    Thinking eHealth: A Mathematical Background of an Individual Health Status Monitoring System to Empower Young People to Manage their Health

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    Author
    Lokshina, Izabella V.
    Bartolacci, Michael R.
    Keyword
    Classes of health situations
    Composition inference rule
    e-Health
    Fuzzy logic
    Identification process
    Individual health status monitoring system
    Masking symptoms
    Mobile monitoring
    Model and Algorithms
    Journal title
    International Journal of Interdisciplinary Telecommunications and Networking
    Date Published
    2014
    
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    URI
    http://hdl.handle.net/20.500.12648/7148
    Abstract
    This paper focuses on a mathematical background of an individual health status monitoring system to empower young people to manage their health. The proposed health status monitoring system uses symptoms observed with mobile sensing devices and prior information about health and environment (provided it exists) to define individual physical and psychological status. It assumes that a health status identification process is influenced by many parameters and conditions. It has a flexible logical inference system providing positive psychological influence on young people since full acceptance of recommendations on their behavioral changes towards healthy lifestyles is reached and a correct interpretation is guaranteed. The model and algorithms of the individual health status monitoring system are developed based on the composition inference rule in Zadeh's fuzzy logic. The model allows us to include in the algorithms of logical inference the possibility of masking (by means of a certain health condition) the symptoms of other health situations as well as prior information (if it exists) regarding health and environment. The algorithms are generated by optimizing the truth of a single natural “axiom”, which connects an individual health status (represented by classes of health situations) with symptoms and matrices of influence of health situations on symptoms and masking of symptoms. The new algorithms are fairly different from traditional algorithms, in which the result is produced in the course of numerous single processing rules. Therefore, the use of a composition inference rule makes a health status identification process faster and the obtained results more precise and efficient comparing to traditional algorithms.
    Citation
    Lokshina, I. V., & Bartolacci, M. R. (2014). Thinking eHealth: A Mathematical Background of an Individual Health Status Monitoring System to Empower Young People to Manage Their Health. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 6(3), 27-36. http://doi.org/10.4018/ijitn.2014070103
    DOI
    10.4018/ijitn.2014070103
    Description
    IGI Global's Fair Use Policy - For Subscription-Based Publications. IGI GLOBAL AUTHORS, UNDER FAIR USE CAN: Post the final typeset PDF (which includes the title page, table of contents and other front materials, and the copyright statement) of their chapter or article (NOT THE ENTIRE BOOK OR JOURNAL ISSUE), on the author or editor's secure personal website and/or their university repository site. (from https://www.igi-global.com/about/rights-permissions/content-reuse/ on 3/3/2022)
    ae974a485f413a2113503eed53cd6c53
    10.4018/ijitn.2014070103
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    School of Liberal Arts and Business - Scholarly and Creative Works
    SUNY Oneonta Scholarly and Creative Works

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