Patient Health Monitoring and Heart Disease Prediction System

Abstract

Nowadays, applications of IoT is everywhere and it is making our life much easier because of its sensor technology, interconnected devices which can collect necessary information and process it. In the past decades, it is seen that many patients die due to heart related diseases due to lack of medical facilities. Due to these applications of IoT, it is having huge applications in medical sector also and with the help of IoT we can get the health parameters of patient using different sensors like temperature sensor, heart rate, blood pressure and SPo2 sensor. So, this paper proposes an idea which can collect all these health parameters from patient and creating a machine learning model using the random forest algorithm which can predict the different types of heart diseases like Coronary artery disease, Angina, Myocardial infraction and Silent Ischemia. Now, patient can come in contact with all these sensors and sensed data will sent to cloud and feed these inputs to machine learning model. This model will predict whether the patient is having any heart disease or not.