Publication Type : Conference Paper
Thematic Areas : Wireless Network and Application
Publisher : Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer Verlag.
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
Keywords : Health care, Hospital data processing, mHealth, Mobile health monitoring, Mobile telecommunication systems, Patient data, remote health monitoring, Sensor data, Smartphones, Wearable sensors
Campus : Amritapuri
School : School of Engineering
Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)
Department : Wireless Networks and Applications (AWNA)
Year : 2016
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.
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.