Abstract
Current telehealth systems are used to improve the treatment of chronic diseases by collecting medical data at the patient and transferring them to a remote medical institution. Research shows that such medical practice can be substantially improved if the measured parameters are greater in number and of more diverse nature. Emerging consumer solutions for monitoring personal health and wellness, as well as various resources from domains like internet, telecommunications and smart living, can be used as possible sources for exploration of an individual’s wider health context. It was our aim to design an internet of things solutions, which would combine these sources of information into context information, complementary to health data. An internet of things platform was designed and implemented and integration with an established e-health system was provided to enrich telehealth data with context information by aggregating and processing cross-domain inputs from various sources. The approach was validated on a use case scenario. The concept was tried in a scenario related to prevention and management of heart disease. The system’s advanced graphic correlation features are expected to help physicians and patients identify true roots of health problems. Medical researchers are also expected to benefit from a deeper insight into complex cross-domain parameter dependencies that determine an individual’s health.
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References
Touati, F., and Tabish, R., U-healthcare system state-of-the-art review and challenges. J. Med. Syst. 37:9949, 2013. doi:10.1007/s10916-013-9949-0.
Scheller-Kreinsen, D., Blümel, M., and Busse, R., Chronic disease management in Europe. Eurohealth. 15(1):1–4, 2009.
Thorpe, K.E., Chronic disease management and prevention in the US: the missing links in health care reform. Eurohealth. 15(1):5–7, 2009.
Fenstermacher, D.A., Wenham, R.M., Rollison, D.E., and Dalton, W.S., Implementing personalized medicine in a cancer center. Cancer J. 17(6):528–536, 2011. doi:10.1097/PPO.0b013e318238216e.
Huh, J., Le, T., Reeder, B., Thompson, H.J., and Demiris, G., Perspectives on wellness self-monitoring tools for older adults. Int. J. Med. Inform. 82:1092–1103, 2013. doi:10.1016/j.ijmedinf.2013.08.009.
Zheng, Y.L., et al., Unobtrusive sensing and wearable devices for health informatics. IEEE Trans. Biomed. Eng. 61(5):1538–1554, 2014.
Pantelopoulos, A., and Bourbakis, N.G., A survey on wearable sensor-based systems for health monitoring and prognosis. Trans. Sys. Man. Cyber. Part C. 40:1–12, 2010. doi:10.1109/TSMCC.2009.2032660.
Swan, M., Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Public Health. 6:492–525, 2009. doi:10.3390/ijerph6020492.
Sysoev, M., Kos, A., and Pogačnik, M., Noninvasive stress recognition considering the current activity. Pers. Ubiquit. Comput. 7(19):1045–1052, 2015. doi:10.1007/s00779-015-0885-5.
Zheng, Y.-L., Ding, X.-R., Poon, C.C.Y., Lo, B.P.L., Zhang, H., Zhou, X.-L., Yang, G.-Z., Zhao, N., and Zhang, Y.-T., Unobtrusive sensing and wearable devices for health informatics. IEEE Trans. Biomed. Eng. 61:1538–1554, 2014. doi:10.1109/TBME.2014.2309951.
Suciu, G., et al., Big data, internet of things and cloud convergence: an architecture for secure E-health applications. J. Med. Syst. 39:141, 2015. doi:10.1007/s10916-015-0327-y.
Volk, M., Sterle, J., and Sedlar, U., Safety and privacy considerations for mobile application Design in Digital Healthcare. Int J Distributed Sensor Networks. 549420(2015):12, 2015. doi:10.1155/2015/549420.
Kerkri, E.M., Quantin, C., Allaert, F.A., Cottin, Y., Charve, P., Jouanot, F., and Yétongnon, K., An approach for integrating heterogeneous information sources in a medical data warehouse. J. Med. Syst. 3(25):167–176, 2001. doi:10.1023/A:1010728915998.
Kos, A. et.al. (2012) Open and scalable IoT platform and its applications for real time access line monitoring and alarm correlation. In: Andreev S, Balandin S, Koucheryavy Y. 12th International Conference, NEW2AN 2012, and 5th Conference, ruSMART 2012, St. Petersburg, Russia, August 27–29, 2012. Internet of things, smart spaces, and next generation networking: proceedings, LNCS. Berlin; Heidelberg: Springer, pp 27–38.
Kos, A., Sedlar, U., Volk, M., Peternel, K., Guna, J., Kovačič, A., Burger, G., Bešter, J., Tomažič, S., and Pogačnik, M., Real-time eHealth visualisation and actuation platform. Int. J. Embed. Syst. 7(2):104–114, 2015. doi:10.1504/IJES.2015.069995.
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Pustišek, M. A System for Multi-Domain Contextualization of Personal Health Data. J Med Syst 41, 16 (2017). https://doi.org/10.1007/s10916-016-0663-6
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DOI: https://doi.org/10.1007/s10916-016-0663-6