Why the study?
The study aimed to address challenges in ubiquitous healthcare monitoring, including mobility, scalability, and network latency.
A proposed Fog-assisted healthcare monitoring framework demonstrated effectiveness in distinguishing abnormal signals and assessing health risks in a cohort of 245 patients.
Should not yet change practice; leaves open randomized validation of fog-assisted monitoring.
In order to tackle some challenges in ubiquitous healthcare monitoring such as mobility, scalability, and network latency, a framework for Fog-assisted healthcare monitoring is proposed in this paper. This framework is composite of body-sensing layer, Fog layer (Fog-assisted gateway), Cloud layer (health Cloud). And then, this paper makes an intensive study in some key technologies of the proposed framework such as an IPv6-based network architecture, intelligent warning model based on subband energy feature, security framework of HL7 RIM-based data exchange, health risk assessment based on fusion of grey model and Markov model. Finally, results of experiment depict that the proposed intelligent warning model can make immediate distinction abnormal signals. Moreover, the proposed health assessment model confirms its effectiveness with respect to 245 patients in Xiamen District of Jimei.
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Hu et al. (2019) studied this question.
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