Abstract
Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation.
Highlights
Cardiovascular diseases (CVD), such as high blood pressure, ischaemic heart disease or arrhythmias, are currently the leading cause of death in the world [1]
In Spain, 28.30% of deaths were related to CVD, according to the latest report published by the National Institute of Statistics (INE) on the causes of death in 2018
It includes a deep learning-based artificial intelligence (AI) algorithm to help the physician make the diagnosis. This tool automatically classifies single short ECG lead records for the detection of Atrial Fibrillation and other heart rhythms. This monitoring system could be especially interesting for patients who live in rural areas or those who require telematic assistance during pandemics, such as the current COVID-19, since it allows the acquisition of bio-signals remotely and avoids the need for a face-to-face consultation
Summary
Cardiovascular diseases (CVD), such as high blood pressure, ischaemic heart disease or arrhythmias, are currently the leading cause of death in the world [1]. Most interactions between a physician and a patient require equipment and devices, including external medical devices, such as glucose monitors; implanted, such as pacemakers; or stationary, such as home monitoring devices and scanners Providing connectivity to these devices makes it possible to create an infrastructure of health systems and services: the internet of medical things (IoMT) [10]. The system is capable of sending the ECG signal to a service located in the Fog layer using the LoRa communication protocol It includes a deep learning-based AI algorithm to help the physician make the diagnosis. This tool automatically classifies single short ECG lead records for the detection of Atrial Fibrillation and other heart rhythms This monitoring system could be especially interesting for patients who live in rural areas or those who require telematic assistance during pandemics, such as the current COVID-19, since it allows the acquisition of bio-signals remotely and avoids the need for a face-to-face consultation
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