Solar powered internet of things-based heart rate monitoring system employing electrocardiogram signal analysis

Abstract

Electrocardiogram (ECG) test is used to record the electrical activity of a human heart for determining any problems with irregular heartbeat patterns and other cardiovascular conditions. This project deals with the implementation of an Internet of things (IoT) enabled ECG monitoring system with solar supply that can identify heart rate deviations from normal values (40 BPM, 80 BPM and 120 BMP) utilizing simulated ECG signals. The ECG data acquisition is done by using KL-76001 biomedical measurement training system, KL-75001 ECG module and multiparameter simulator MS400. The acquired ECG signals are processed through Python software to detect R-peaks and R-R interval. The counts of these R-R peaks are utilized in conjunction with the Blynk IoT platform, employing an ESP8266 module for monitoring via a mobile application and LCD display. The system was tested for detecting and monitoring three heart conditions which are bradycardia, normal, and tachycardia and successfully demonstrated alert capabilities for these conditions.