An IoT Enabled Heart Disease Monitoring System Using Grey Wolf Optimization and Deep Belief Network

Abstract

Heart disease is a deadly disease today irrespective of age group among people because they are not aware about their heart disease level, and the kind of heart diseases. It is necessary to aware about their type of heart diseases and the regular disease monitoring process in this quick world. This paper proposes a new heart disease monitoring system with the incorporation of Internet of Things and Deep Learning technique for safeguarding the patients. Here, a new feature selection algorithm which is incorporated for performing better classification through deep learning algorithm. In this proposed heart disease monitoring system, we monitor the disease level according to the inputs that are given to the IoT devices. Moreover, it classifies the patient details according to the heart disease types and the severity of the disease. Finally, it gives alarm/message to the patients according to the type of heart disease with the available inputs. The experiments have been demonstrated and proved as the proposed system is better in terms of prediction accuracy.