An Efficient Computational Approach for Phonocardiogram Signals Analysis and Normal/Abnormal heart sounds diagnosis

Abstract

In the present work, the authors proposed of cardiac sound signals (ANN) is executed as indicator and classifier of PCG abnormalities using the features extracted from PCG acoustic signals via the discrete wavelet transform (DWT). To develop and validate the proposed approach, the PASCAL CHSC 2011 dataset was utilized. The assess the efficiency of the proposed intelligent approach. The results demonstrate that the approach achieves a high performance compared to other classificat results showed an overall accuracy with the recently published ones that achieved utilizing different machine learning (ML) approaches. The achieved results showed that the PCG acoustic signals. cardiovascular abnormalities.