IEEE Communications Magazine · 2017 · 274 citations · 11 references
ComputingCloud ComputingHealth InformaticsCloud InfrastructureHealthcare Information SystemsInternet Of ThingsCardiovascular MonitoringHealth Monitoring SystemsHealthcare Internet Of ThingsHealthcare Iot ArchitectureHeart Rate MonitoringHeartbeat MonitoringPervasive Health MonitoringReal-time MonitoringRemote Patient MonitoringRemote Patient Monitoring Systems
Rising healthcare costs and patients’ preference for home care have spurred research into remote monitoring solutions, yet current approaches lack flexibility, scalability, and energy efficiency. This work introduces a pervasive patient health monitoring (PPHM) system infrastructure. PPHM integrates cloud computing with Internet‑of‑Things devices and is demonstrated through a real‑time ECG monitoring case study of a congestive heart failure patient. Experimental results confirm that the PPHM system is flexible, scalable, and energy‑efficient for remote patient monitoring.
The exponentially growing healthcare costs coupled with the increasing interest of patients in receiving care in the comfort of their own homes have prompted a serious need to revolutionize healthcare systems. This has prompted active research in the development of solutions that enable healthcare providers to remotely monitor and evaluate the health of patients in the comfort of their residences. However, existing works lack flexibility, scalability, and energy efficiency. This article presents a pervasive patient health monitoring (PPHM) system infrastructure. PPHM is based on integrated cloud computing and Internet of Things technologies. In order to demonstrate the suitability of the proposed PPHM infrastructure, a case study for real-time monitoring of a patient suffering from congestive heart failure using ECG is presented. Experimental evaluation of the proposed PPHM infrastructure shows that PPHM is a flexible, scalable, and energy-efficient remote patient health monitoring system.
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BodyCloud: A SaaS approach for community Body Sensor Networks
Giancarlo Fortino, Daniele Parisi, Vincenzo Pirrone et al. · Future Generation Computer Systems · 2013 · 256 citations · Full text