Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG Signal

Abstract

As per American Heart Association information, every year 125 babies out of 1000 are born with congenital heart disease (CHD). It was estimated that 36000 children are live born with CHD each year in the European Union. Child with CHD may have hole in heart up to 3–5 mm as small defects and for large defects it may go up to 5–8 mm. Depending upon the size of hole in the upper or lower chamber of heart shows diseases such as atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus arteriosus (PDA) and tetralogy of Fallot (TOF). Child patients with CHD report difficulties in several areas of daily life such as sports, study, travelling, and driving. It affects the efficiency and functionality of heart. It also affects the autonomic control of heart rate. The main focus would be to detect CHD in the pediatric population and preventive measures that can be proposed to improve the quality of life. Nowadays, we still fill infancy in the analysis of pediatric ECG. In our research work, we aimed at wave detection of CHD and its ECG analysis with different classification techniques so that child with CHD can be diagnosed accurately. We then attempted to justify the recommendation for promising future directions in signal processing and database creation