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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Fitbit Flex (2014), http://www.fitbit.com/flex (accessed: October 22, 2014)
Jawbone Up (2014), https://jawbone.com/up (accessed: October 22, 2014)
Mining Minds Project (2014), http://www.miningminds.re.kr/
Withings Pulse (2014), http://www.withings.com/es/withings-pulse.html (accessed: October 22, 2014)
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)
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)
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)
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)
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)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Banos, O. et al. (2015). An Innovative Platform for Person-Centric Health and Wellness Support. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2015. Lecture Notes in Computer Science(), vol 9044. Springer, Cham. https://doi.org/10.1007/978-3-319-16480-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-16480-9_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16479-3
Online ISBN: 978-3-319-16480-9
eBook Packages: Computer ScienceComputer Science (R0)