A Cloud Based Risk Prediction of Coronary Heart Disease

Abstract

Heart attacks claim the lives of thousands of individuals every year. Unfortunately, due to the late notice of the assault, we were unable to preserve the lives of any human beings. In this research, a prototype programme for Android devices has been built by integrating clinical data acquired from patients into the software. This portable technology continually collects ECG signals from patients and compares them to values stored in a database to determine whether there is any abnormality in the signals. Risks are categorised into three categories: low, medium, and high. These values are updated in the cloud for ease of observation by medical practitioners, allowing them to assist patients by forecasting cardiac disease before it manifests itself in the first place. An email is also sent to the patient's caretaker to inform them of the risk criteria that the patient is likely to have. This strategy educates individuals on the need of seeing a cardiologist in order to avert unexpected death.