Prenatal identification of CHD murmur using four segment phonocardiographic signal analysis

Congenital heart defects (CHD) are one of the utmost birth defects present in the neonatal after birth and a big challenge for the researchers to identify the structural abnormality during the antepartum period. An algorithm is presented here to identify the presence of CHD through foetal phonocardiographic (fPCG) signals. The recorded fPCG is decomposed using Daubechies4 wavelet with sub-level threshold to remove the noise in the signal. The Shannon energy is used to identify the different peaks of signals and then S1 and S2 according to the intervals between adjacent peaks. The signal is segmented into four important parts: S1, S1S2, S2 and S2S1. The FFT is used to identify the frequency component present in four segments which in turn indicates the presence of pathological murmur that may turn into CHD. The algorithm is tested on 25 samples with accuracy rate 88% in identifying the presence of a murmur.