An Innovative Platform for Person-Centric Health and Wellness Support

  • Oresti Banos
  • Muhammad Bilal Amin
  • Wajahat Ali Khan
  • Muhammad Afzel
  • Mahmood Ahmad
  • Maqbool Ali
  • Taqdir Ali
  • Rahman Ali
  • Muhammad Bilal
  • Manhyung Han
  • Jamil Hussain
  • Maqbool Hussain
  • Shujaat Hussain
  • Tae Ho Hur
  • Jae Hun Bang
  • Thien Huynh-The
  • Muhammad Idris
  • Dong Wook Kang
  • Sang Beom Park
  • Hameed Siddiqui
  • Le-Ba Vui
  • Muhammad Fahim
  • Asad Masood Khattak
  • Byeong Ho Kang
  • Sungyoung Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9044)

Abstract

Modern digital technologies are paving the path to a revolutionary new concept of health and wellness care. Nowadays, many new solutions are being released and put at the reach of most consumers for promoting their health and wellness self-management. However, most of these applications are of very limited use, arguable accuracy and scarce interoperability with other similar systems. Accordingly, frameworks that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these systems are particularly required. This work introduces Mining Minds, an innovative framework that builds on some of the most prominent modern digital technologies, such as Big Data, Cloud Computing, and Internet of Things, to enable the provision of personalized healthcare and wellness support. This paper aims at describing the efficient and rational combination and interoperation of these technologies, as well as their integration with current and future personalized health and wellness services and business.

Keywords

Human behavior Context-awareness Big data Big information Big knowledge Cloud computing Quantified self Digital health Health devices Social networks User interface User experience Knowledge bases Personalized recommendations 

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References

  1. 1.
    Fitbit Flex (2014), http://www.fitbit.com/flex (accessed: October 22, 2014)
  2. 2.
    Jawbone Up (2014), https://jawbone.com/up (accessed: October 22, 2014)
  3. 3.
    Mining Minds Project (2014), http://www.miningminds.re.kr/
  4. 4.
    Withings Pulse (2014), http://www.withings.com/es/withings-pulse.html (accessed: October 22, 2014)
  5. 5.
    Banos, O., Garcia, R., Holgado-Terriza, J.A., Damas, M., Pomares, H., Rojas, I., Saez, A., Villalonga, C.: mHealthDroid: A novel framework for agile development of mobile health applications. In: Pecchia, L., Chen, L.L., Nugent, C., Bravo, J. (eds.) IWAAL 2014. LNCS, vol. 8868, pp. 91–98. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  6. 6.
    Banos, O., Villalonga, C., Damas, M., Gloesekoetter, P., Pomares, H., Rojas, I.: Physiodroid: Combining wearable health sensors and mobile devices for a ubiquitous, continuous, and personal monitoring. The Scientific World Journal 2014(490824), 1–11 (2014)CrossRefGoogle Scholar
  7. 7.
    Fortino, G., Giannantonio, R., Gravina, R., Kuryloski, P., Jafari, R.: Enabling effective programming and flexible management of efficient body sensor network applications. IEEE Transactions on Human-Machine Systems 43(1), 115–133 (2013)CrossRefGoogle Scholar
  8. 8.
    Gaggioli, A., Pioggia, G., Tartarisco, G., Baldus, G., Corda, D., Cipresso, P., Riva, G.: A mobile data collection platform for mental health research. Personal Ubiquitous Comput. 17(2), 241–251 (2013)CrossRefGoogle Scholar
  9. 9.
    Oresko, J.J., Jin, Z., Cheng, J., Huang, S., Sun, Y., Duschl, H., Cheng, A.C.: A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing. IEEE Transactions on Information Technology in Biomedicine 14(3), 734–740 (2010)CrossRefGoogle Scholar
  10. 10.
    Patel, S., Mancinelli, C., Healey, J., Moy, M., Bonato, P.: Using wearable sensors to monitor physical activities of patients with copd: A comparison of classifier performance. In: Proceedings of 6th International Workshop on Wearable and Implantable Body Sensor Networks, Washington, DC, USA, pp. 234–239 (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Oresti Banos
    • 1
  • Muhammad Bilal Amin
    • 1
  • Wajahat Ali Khan
    • 1
  • Muhammad Afzel
    • 1
  • Mahmood Ahmad
    • 1
  • Maqbool Ali
    • 1
  • Taqdir Ali
    • 1
  • Rahman Ali
    • 1
  • Muhammad Bilal
    • 1
  • Manhyung Han
    • 1
  • Jamil Hussain
    • 1
  • Maqbool Hussain
    • 1
  • Shujaat Hussain
    • 1
  • Tae Ho Hur
    • 1
  • Jae Hun Bang
    • 1
  • Thien Huynh-The
    • 1
  • Muhammad Idris
    • 1
  • Dong Wook Kang
    • 1
  • Sang Beom Park
    • 1
  • Hameed Siddiqui
    • 1
  • Le-Ba Vui
    • 1
  • Muhammad Fahim
    • 2
  • Asad Masood Khattak
    • 3
  • Byeong Ho Kang
    • 4
  • Sungyoung Lee
    • 1
  1. 1.Department of Computer EngineeringKyung Hee UniversityKorea
  2. 2.Department of Computer EngineeringIstanbul Sabahattin Zaim UniversityTurkey
  3. 3.College of Technological InnovationZayed UniversityUAE
  4. 4.School of Computing and Information SystemsUniversity of TasmaniaAustralia

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