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June 24, 20220 citations

A Review on IoT-Driven Technologies for Heart Disease Diagnosis and Prediction

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MSMakarand ShahadeMGMangesh Ghonge

Key Result

This review highlights various IoT-driven technologies and wireless body area networks utilized in the literature for the continuous remote monitoring, diagnosis, and prediction of heart disease.

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IoT-driven technologies for heart disease diagnosis and prediction

This review summarizes the current literature on IoT-driven technologies and wireless body area networks for continuous remote cardiac monitoring and heart disease prediction.

Abstract

People around the world are at risk from chronic diseases like cancer, heart disease, and diabetes. When it comes to sudden cardiac arrest, many people have recently become increasingly concerned. The main cause of death in the world is heart disease. Because it needs both experience and advanced knowledge, predicting heart disease is a difficult assignment. Sensor values are being collected for heart disease detection and prediction using internet of things (IoT), which has recently been implemented in healthcare systems. In order to achieve a continuous remote cardiac monitoring system, IoT and wireless technology have advanced significantly over the past several years. The use of various sensors, such as electrocardiograms (ECGs), thermometers, and blood pressure monitors to collect important body signals and diagnose illnesses has resulted in the creation of a wireless body area network. The diagnosis of cardiac disease findings is low in accuracy. The goal is to highlight IoT-driven technologies that have been used in the literature for diagnosing and forecasting heart disease.

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Shahade et al. (2022) conducted a review in Heart disease. IoT-driven technologies was evaluated. This review highlights various IoT-driven technologies and wireless body area networks utilized in the literature for the continuous remote monitoring, diagnosis, and prediction of heart disease.

synapsesocial.com/papers/6a242f3d98edd3e1959efb5dhttps://doi.org/10.4018/978-1-7998-8443-9.ch002
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