Publication Type : Journal Article
Publisher : Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Source : Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer Verlag, Volume 192, p.168-176 (2017)
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
Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)
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.
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.