Variational mode decomposition based automated fetal PCG denoising and extraction

Congenital cardiac anomalies of fetus are often characterized by the unprecedented changes in the auditory properties of cardiac sounds occurs during the gestation period of pregnant women. These abnormalities are often seen in inconsistent patterns of heart sounds that are driven by asynchronous variations in heart rates of mother and fetus. This hostile situation becomes severe if it is untreated and might threaten to life risk in pregnant women. In this work, we proposed a novel and automated signal processing paradigm using Variational Mode Decomposition (VMD) to detect and extract the mother and fetus heart sounds from the raw PCG signals recorded from outer surface of the maternal abdomen. The proposed framework constitutes a couple of cascaded VMD blocks: The first VMD block alleviates the raspatory noises and other artifacts from the raw PCG signal; while the Next one, decomposes the mother and fetus heart sounds obtained from its preceding block. A publicly available Shiraz University Fetal Heart Sounds Database is used to test the efficacy of the proposed model. In addition, noisy PCG corpus characterized by the additive white gaussian noise is used to test the efficacy of the proposed network. F