IoT based ECG System for Arrhythmia Detection using Telemetry Monitoring

An electrocardiogram (ECG) is the primary signal used for the detection of any cardiovascular abnormalities, but conventional clinical ECG scans include restrained time-duration ECG signals, lacking the asymptomatic or essential attributes of CVDs. Therefore, developing a system for real-time and long-term ECG monitoring is crucial for the early diagnosis of CVDs. With technological advancements in the field of wearable electronics and IoT innovations, developing a system for convenient and long-term ECG monitoring is easily possible. In this paper, we suggest a new approach for ECG measurement centered on Internet of Things (IoT) schemes that can facilitate long-term monitoring. The required ECG information is acquired utilizing a wearable observing node consisting of an AD8232 ECG sensor with AgCl gel based electrodes. The conditioned ECG signal is transmitted to the IoT cloud utilizing Wi-Fi technology. We have used the Node MCU ESP8266 Wi-Fi module to transmit the ECG data to the IoT cloud and the Blynk 2.0 as an IoT platform to display that data. The program code was developed to acquire ECG waves along with important features like R-R interval, QRS duration, PR interval, QT interval, HRV, and heart rate. These important diagnostic parameters are displayed on the IoT channel with the required ECG information for the patient and medical professionals. It can be used by medical experts anywhere across the globe to analyze and diagnose the cardiac health conditions of the subjects under investigation and may provide necessary emergency health assistance. The obtained results on the Blynk IoT channel are compared with the clinical ECG of the same subject; the results are acceptable with accuracy of more than 95%, and in compliance with the standard ECG. It can be used for the detection of arrhythmia conditions. We believe the developed system is a positive contribution to telemedicine.