Mining Human Behavior for Health Promotion
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Transcript of Mining Human Behavior for Health Promotion
Mining Human Behavior for Health Promotion
Oresti Banos, Jaehun Bang, Taeho Hur, Muhammad Hameed Siddiqi,
Huynh-The Thien, Le-Ba Vui, Wajahat Ali Khan, Taqdir Ali, Claudia Villalonga, and Sungyoung Lee
Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Korea
{oresti,[…],sylee}@oslab.khu.ac.kr
The monitoring of human lifestyles has gained much attention in the recent years. This work presents a novel approach to combine multiplecontext-awareness technologies for the automatic analysis of people’s conduct in a comprehensive and holistic manner. Activityrecognition, emotion recognition, location detection, and social analysis techniques are integrated with ontological mechanisms as part of aframework to identify human behavior. Key architectural components, methods and evidences are described in this paper to illustrate theinterest of the proposed approach.
Keywords: Digital health, quantified self, context-awareness, activity recognition, emotion recognition, location detection, social analysis
Abstract
“The Slow-Moving Public Health Disaster”
“Collection of innovative services, tools, and techniques, workingcollaboratively to investigate on human's daily-life routines data generatedfrom heterogeneous resources, for personalized wellbeing and healthcaresupport”:
Mining Minds: a Novel Digital Health Framework
The information curation process consists in converting the dataobtained from the user interaction with the real and cyberworld, intoabstract concepts or categories, such as physical activities, emotionalstates, locations and social patterns, which are intelligently combinedto determine and track the user context and behavior:
Information Curation for Behavior Mining
This work was supported by the Industrial Core Technology Development Program (10049079, Development of miningcore technology exploiting personal big data) funded by the Korean Ministry of Trade, Industry and Energy.
Acknowledgements
Diseases linked to lifestyle choices are currently thebiggest cause of death worldwide:• Cardiovascular conditions, cancers, chronic respiratory
disorders, obesity and diabetes, represent more than 60% ofglobal deceases, half of which are of premature nature
• Most of these diseases are fairly associated to common riskfactors, namely, tobacco and alcohol use, unwholesome dietand physical inactivity
• This "lifestyle disease" epidemic causes a much greaterpublic health threat than any other epidemic known to man
• Millions of lives could be saved if the world over the nextdecade invests $1-3 per person on promoting healthier habits
Inferred High Level Context
Inferred Low Level Contexts
Office Work
Curated Data
Sitting Neutral Office