Early prediction of cardiac arrest using ECG signal through IoT

This project mainly aims at developing a cardio arrest monitoring device. The device is designed to evaluate and display 3 parameters namely heart rate, body temperature and pulse rate in real time. The main advantage of the hardware is it is cost effective and specifically small size so that it work on daily basis. Individuals with history of attack will have a continual change in heart rate and body temperature. The fluctuation varies throughout time periods of one or even two weeks. The data obtained from the individuals will be displayed on the device and if the values displayed in the device are abnormal then the individuals are warned. Thus the chances of cardiac arrest can be predicted.