Publication Type:

Journal Article

Source:

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer Verlag, Volume 192, p.168-176 (2017)

ISBN:

9783319588766

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020870045&doi=10.1007%2f978-3-319-58877-3_23&partnerID=40&md5=397bba4a925ad2ab30c5c256fa92efc0

Keywords:

Health care, Hospital data processing, mHealth, Mobile health monitoring, Mobile telecommunication systems, Patient data, remote health monitoring, Sensor data, Smartphones, Wearable sensors

Abstract:

We have developed a rapid remote health monitoring architecture called RASPRO using wearable sensors and smartphones. RASPRO’s novelty comes from its techniques to efficiently compute compact alerts from sensor data. The alerts are computationally fast to run on patients’ smartphones, are effective to accurately communicate patients’ severity to physicians, take into consideration inter-sensor dependencies, and are adaptive based on recently observed parametric trends. Preliminary implementation with practicing physicians and testing on patient data from our collaborating multi-specialty hospital has yielded encouraging results. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017.

Notes:

cited By 0; Conference of 6th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2016 ; Conference Date: 14 November 2016 Through 16 November 2016; Conference Code:192949

Cite this Research Publication

E. Rangan and Rahul K Pathinarupothi, “Adaptive motif-based alerts for mobile health monitoring”, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 192, pp. 168-176, 2017.

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