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The Mining Minds digital health and wellness framework

Overview of attention for article published in BioMedical Engineering OnLine, July 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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7 X users
facebook
1 Facebook page

Citations

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51 Dimensions

Readers on

mendeley
195 Mendeley
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Title
The Mining Minds digital health and wellness framework
Published in
BioMedical Engineering OnLine, July 2016
DOI 10.1186/s12938-016-0179-9
Pubmed ID
Authors

Oresti Banos, Muhammad Bilal Amin, Wajahat Ali Khan, Muhammad Afzal, Maqbool Hussain, Byeong Ho Kang, Sungyong Lee

Abstract

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people's conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems. This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people's lifestyles and provide a variety of smart coaching and support services. This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework. Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 194 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 38 19%
Student > Ph. D. Student 26 13%
Student > Doctoral Student 19 10%
Student > Bachelor 18 9%
Researcher 17 9%
Other 31 16%
Unknown 46 24%
Readers by discipline Count As %
Computer Science 48 25%
Medicine and Dentistry 18 9%
Engineering 14 7%
Business, Management and Accounting 11 6%
Psychology 11 6%
Other 35 18%
Unknown 58 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 October 2019.
All research outputs
#6,015,822
of 22,880,691 outputs
Outputs from BioMedical Engineering OnLine
#150
of 823 outputs
Outputs of similar age
#100,398
of 355,956 outputs
Outputs of similar age from BioMedical Engineering OnLine
#3
of 12 outputs
Altmetric has tracked 22,880,691 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 823 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 355,956 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.