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)