A Wireless ECG Monitoring and Analysis System Using the IoT Cloud

Abstract

A portable electrocardiogram (ECG) monitoring system is essential for elderly and remote patients who are not able to visit the hospital regularly. The system connects a patient to his/her doctor through an Internet of Things (IoT) cloud server that provides all the information needed to diagnose heart diseases. Patients use an ECG monitoring device to collect and upload information regarding their current medical situation via the Message Queue Telemetry Transport (MQTT) protocol to the server. The IoT cloud server performs further analysis that can be useful for both the doctor and the patient. Moreover, the proposed system has an alert mechanism that sends notifications when a certain threshold is reached. The monitoring system accepts two types of input data: real-time data that are collected by an ECG device and benchmark data from the PhysioNet ECG-ID database. The system framework has four components: input, embedded device, IoT cloud server, and interface. Herein, two experiments are conducted using both types of input data. The results show that the proposed system provides reliable and trusted results that might reduce the number of required hospital visits. A comparison between the proposed system and several techniques previously reported in the literature is conducted. Finally, an implementation of the proposed system is presented to illustrate its operation.

IoT-based health information system using MitApp for abnormal electrocardiogram signal monitoring

“…The AD8232 sensor is a signal conditioning block capable of extracting, filtering, and amplifying the body's highly noisy biopotential signals. The sensor gets this biopotential signal input through electrodes placed on certain body parts based on Einthoven's triangle bipolar lead theory [20]. The sensor gets this biopotential signal input through electrodes placed on certain body parts based on Einthoven's triangle bipolar lead theory [20].…”

“…The sensor gets this biopotential signal input through electrodes placed on certain body parts based on Einthoven's triangle bipolar lead theory [20]. The sensor gets this biopotential signal input through electrodes placed on certain body parts based on Einthoven's triangle bipolar lead theory [20]. The sensor is based on the 3-lead ECG technique, which uses a yellow electrode with a positive pole, a red electrode with a negative pole, and a green electrode as ground with an analog signal reading output.…”