ECG AND PULSE OXYGEN LEVEL MONITORING AND ARRHYTHMIA CLASSIFICATION USING CNN

Abstract

Early Diagnosis of disease has always been a boon for the treatment of any disease. However, for people living in remote areas, health facilities have not been easily accessible. A few of the critical parameters for determining whether the person is healthy or not depend on a few health parameters such as Heart Rate, electrocardiogram (ECG), oxygen saturation (SpO2), and Body Temperature. To avoid overcrowding hospitals, we have developed a remote monitoring and prediction system. We have developed Arduino-based low-cost hardware that can be used for telemedicine service and remote monitoring of patients in India directly from expert doctors in the field. The system was successfully tested and got around 97 percent successful transmission of data without latency. The model includes a web app that directly reports the data to the doctors and has been trained with many machine learning models to predict abnormal patterns. Ultimately the web app gives a composite score based on heart rate and arrhythmia to facilitate subjects for heart health. Created a system, which is the dynamic web app to display real-time data and plot the graph of the variation dynamically. Using this system to check our health periodically makes it possible to reduce the chances of deteriorating health conditions