Smart ECG Monitoring Through IoT

Smart ECG Monitoring Through IoT

Ibtihel Nouira (Technology and Medical Imaging Laboratory, Medicine Faculty of Monastir, University of Monastir, Tunisia) and Mohamed Hadj Said (Higher Institute of Computer Science and Mathematics, University of Monastir, Tunisia)
Copyright: © 2020 |Pages: 23
DOI: 10.4018/978-1-7998-0261-7.ch010


The emergence of internet of things allows the integration of health systems by enabling real-time monitoring with a low cost. Therefore, one of the essential targets in this work is the realization of a new smart real-time electrocardiogram remote monitoring system based on cloud networks. This health wireless system allows the acquisition of electrocardiogram signal with the temperature and acceleration measurement of the patient's body using the inertial measurement unit module sensor. A strong access schemes is employed to transfer the data from sensors to cloud environment by keeping the protection of e-health information. The second objective in this chapter is designing a flexible and stretchable health circuit basing on design considerations, aiming the combination of flexible, elastic, and rigid materials around minimal constraints and maximum mechanical dependability in the structures. The flexible fabrication part was inspired from the biocompatible process technology.
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Recently, several studies have been interested in developing systems for remote monitoring of cardiac signals (Yang et al, 2016; Xia et al, 2013; Manikandan et al, 2019). In fact, the arrival of the Internet of Things (IoT) allows driving the development of large advanced information services, which requires the treatment in real-time and the storage of data centers with a great capacity and computing power (Chakraborty et al, 2016). In addition to that, the rapid growth of the (IoT) has led to the development of a multitude of new access technologies targeted at low power- wide area networks (LP-WANs). For example, sensors and monitoring solutions can exchange very small data rate and very little energy consumption can be considered as the typical applications for the LPWAN (Qadir et al, 2018; Rashid et al, 2016). In addition, the arrival of new processing technologies in the field of biomedical engineering allows for a considerable development. More specifically, the emergence of the field of artificial intelligence and its integration with IoT applications makes it possible to innovate automatic tools that help real-time medical diagnosis in the development of therapeutic strategies and follow-up care (Rashid et al, 2016; Rashid et al, 2018).

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