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Mining minds: an innovative framework for personalized health and wellness support


Banos, O and Amin, MB and Khan, WA and Ali, T and Afzal, M and Kang, BH and Lee, S, Mining minds: an innovative framework for personalized health and wellness support, Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health), 20-23 May 2015, Istanbul, Turkey, pp. 1-8. ISBN 9781631900457 (2015) [Refereed Conference Paper]

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Copyright Statement

Copyright 2015 ICST

DOI: doi:10.4108/icst.pervasivehealth.2015.259083


The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower people in their self-management as well as to enhance traditional care procedures. While substantial domain-specific contributions have been provided to that end in the recent years, there is a clear lack of platforms that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these technologies. This work presents Mining Minds, an innovative framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized healthcare and wellness support. Mining Minds embraces some of the currently most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, and state of- the-art concepts and methods, such as Context-Awareness, Knowledge Bases or Analytics, among others. This paper aims at thoroughly describing the efficient and rational combination and interoperation of these modern technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support.

Item Details

Item Type:Refereed Conference Paper
Keywords:digital health, human behavior, quantified-self, big data, cloud computing, context-awareness, knowledge bases, user experience
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Amin, MB (Dr Muhammad Bilal Amin)
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:106692
Year Published:2015
Web of Science® Times Cited:17
Deposited By:Information and Communication Technology
Deposited On:2016-02-17
Last Modified:2021-03-25

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