Heart Health Monitoring Using IoT and Machine Learning Methods

Abstract

The goal of this effort is to propose a real-time IoT based heart health monitoring system that combines location and vital sign sensors to enable remote patient health status monitoring and heart health prediction using a variety of machine learning techniques. We proposes a pre-processing performance to increase the classification accuracy of ECG signal. An Arduino-based real-time Heart Health monitoring system that measures vital signs like heart rate, body temperature, humidity, and ECG was created and demonstrated. The system that was developed can send recorded data, which is updated every 10 seconds, to a central server.