A mobile system for real-time context-aware monitoring of patients' health and fainting Online publication date: Tue, 21-Oct-2014
by Giovanna Sannino; Giuseppe De Pietro
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 10, No. 4, 2014
Abstract: Patient context awareness is an important concept for application services in mHealth environments. In this paper we present a multi-sensors system that uses a rule-based DSS able to enhance the accuracy of potentially dangerous heart rate variability by taking into account patient context information. In addition the proposed system is able to detect also patient falls in real time. We have designed and implemented an intelligent, user-friendly, and context-aware system that allows receiving data from several sensors and provides the computational power for context recognition. We also show that the use of an intelligent approach relying on a rule-based DSS for the analysis of data and vital signs is better than approaches missing either DSS or context-awareness. Finally, the paper also describes a case study where the system has revealed important benefits for both patients and medical staff.
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