Early Detection of Pediatric Heart Disease by Automated Spectral Analysis of Phonocardiogram in Children

Congenital heart disease is now the most common severe congenital abnormality found in live births and the cause of more than half the deaths from congenital anomalies in childhood. Heart murmurs are often the first signs of pathological changes of the heart valves, and they are usually found during auscultation in the primary health care. Auscultation is widely applied in clinical activity; nonetheless sound interpretation is dependent on clinician training and experience. Distinguishing a pathological murmur from a physiological murmur is difficult and prone to error. To address this problem we have devised a simplified approach to pediatric cardiac scanning. This will not detect all forms of congenital heart disease but will help in the diagnosis of many defects. Cardiac auscultatory examinations of 93 children were recorded, digitized, and stored along with corresponding echocardiographic diagnoses, and automated spectral analysis using discrete wavelet transforms was performed. Patients without heart disease and either no murmur or an innocent murmur (n = 40) were compared to patients with a variety of cardiac diagnoses and a pathologic systolic murmur present (n = 53). A specificity of 100% and a sensitivity of 90.57% were achieved using signal processing techniques and a k-nn as classifier.

Keywords:

Phonocardiogram (PCG) , Murmur , Cardiac , K-nn Classifier , Pediatric , Wavelet