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Authors: Zilu Liang and Mario Alberto Chapa Martell

Affiliation: The University of Tokyo, Japan

Keyword(s): Self Health Care, Preventive Health Care, Personal Analytics, Quantified Self, Framework.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Design and Development Methodologies for Healthcare IT ; Devices ; e-Health for Public Health ; Health Information Systems ; Healthcare Management Systems ; Human-Computer Interaction ; Pervasive Health Systems and Services ; Physiological Computing Systems ; Wearable Sensors and Systems

Abstract: Preventive health care is considered a promising solution to the prevalence of chronic diseases. Nevertheless, preventive health care at the population-level adopts an one-fit-all approach. We intend to solve the problem through promoting preventive health care at the individual level based on self-quantification. Nowadays millions of people are tracking their health conditions and collecting huge quantity of data. We propose a Preventive Health care on Individual Level (PHIL) framework that guides people to leverage their self-tracking data to improve personal health, which forms a data-driven but objective-oriented methodology. The PHIL framework consists of five phases: Define, Track, Analyze, Improve and Control (DTAIC), covering the whole process of a complete self health care project. While the proposed PHIL framework can be implemented to achieve various health benefit, we selectively present one case study where the subject designed and conducted a self health care p roject for sleep quality improvement under the PHIL framework. We hope the proposed framework can help change the passive role of health care receivers in traditional health care system, and empower people to actively participate in the health care ecosystem and take the initiative in managing and improving personal health. (More)

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Paper citation in several formats:
Liang, Z. and Chapa Martell, M. (2015). Framing Self-quantification for Individual-level Preventive Health Care. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF; ISBN 978-989-758-068-0; ISSN 2184-4305, SciTePress, pages 336-343. DOI: 10.5220/0005202503360343

@conference{healthinf15,
author={Zilu Liang. and Mario Alberto {Chapa Martell}.},
title={Framing Self-quantification for Individual-level Preventive Health Care},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF},
year={2015},
pages={336-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005202503360343},
isbn={978-989-758-068-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF
TI - Framing Self-quantification for Individual-level Preventive Health Care
SN - 978-989-758-068-0
IS - 2184-4305
AU - Liang, Z.
AU - Chapa Martell, M.
PY - 2015
SP - 336
EP - 343
DO - 10.5220/0005202503360343
PB - SciTePress