A New Heart Sound Signal Identification Approach Suitable for Smart Healthcare Systems

Currently, proliferation of the Internet of Things development has fostered several research efforts and works in smart healthcare systems. One of the important area is the development of automated systems to identify fundamental heart sound signals in the presence of noise and murmur. In this work, we proposed a new scheme for the fundamental heart sound signals identification and murmur by firstly employing the CEEMD algorithm combined with the Pearson distance metric and secondly utilizing the Shannon energy envelope to segment the first fundamental heart sound signal, S1 the second fundamental heart sound signal, S2, and murmur. Here, the CEEMD algorithm and the Pearson distance metric perform signal decomposition to extract murmur from the heart sound signals while the Shannon energy envelope increases the quality of signal features. Based on our evaluation the proposed algorithm showed promising result to identify the S1 and S2 in the presence of murmur. The algorithm at the same time can trace the duration and location of the murmur.