Predictive Heart Rate Monitoring System

The increased frequency of long-term sickness along with the widespread impact of cardiovascular diseases as a primary cause of death have become a common concern nowadays and emphasize the necessity for easily accessible, real-time health monitoring and early detection. There is a specific product in front of us that we are going to talk about now which is about an advanced set of hardware components and algorithms to give the user an opportunity to predict their own heart health. This system is manufactured in the form of an AmazingMAX30100 sensor and NodeMCU microcontroller that are taken as physical entities that are measuring the patient's health proportions like heart rate and oxygen saturation (SpO₂) which in turn are shown on an OLED screen in real-time for the patient and at the same time are sent to a cloud platform for the physician to follow on remotely. A data science-driven software further strengthens the proposed system, by employing the latest techniques in machine learning such as Random Forest, Decision Tree, Support Vector Machine, and Logistic Regression to seek out the sources of heart disease, if any. It goes beyond this by also embodying a simple web application to give users the power of full interaction with the system and with each stage, i.e. inputting their own data into the system, accessing their health parameters, getting real-time information and accessing their individual risk.