Abstract
Phonocardiography is a non-invasive technique for the detection of fetal heart sounds (fHSs). In this study, analysis of fetal phonocardiograph (fPCG) signals, in order to achieve fetal heartbeat segmentation, is proposed. The proposed approach (namely WT–FD) is a wavelet transform (WT)-based method that combines fractal dimension (FD) analysis in the WT domain for the extraction of fHSs from the underlying noise. Its adoption in this field stems from its successful use in the fields of lung and bowel sounds de-noising analysis. The efficiency of the WT–FD method in fHS extraction has been evaluated with 19 simulated fHS signals, created for the present study, with additive noise up to (3 dB), along with the simulated fPCGs database available at PhysioBank. Results have shown promising performance in the identification of the correct location and morphology of the fHSs, reaching an overall accuracy of 89% justifying the efficacy of the method. The WT–FD approach effectively extracts the fHS signals from the noisy background, paving the way for testing it in real fHSs and clearly contributing to better evaluation of the fetal heart functionality.
Highlights
Fetal heart rate observation is important for proper fetal well-being assessment during the period of pregnancy
It shows that the fractal dimension (FD) method successfully detects the location of the sounds by using the binary sequences, and it separates the non-stationary bioacoustics signal from the stationary background noise
The above three indices were calculated for the evaluation of the testing wavelet transform (WT)–FD method, and the results are presented in Section “Results”
Summary
Fetal heart rate (fHR) observation is important for proper fetal well-being assessment during the period of pregnancy. The present study was motivated from a previously proposed method of Hadjileontiadis for the separation of lung and bowel sounds from the background noise (Hadjileontiadis, 2005) The latter technique uses a scheme of WT for de-noising the signals and fractal dimension (FD) analysis for the detection of lung and bowel sounds. It shows that the FD method successfully detects the location of the sounds by using the binary sequences, and it separates the non-stationary bioacoustics signal from the stationary background noise. A criterion of each estimated fetal heartbeat amplitude and the distance between fetal heart cycles is considered for better decision between S1 and S2 beat. The SNR values were computed according to the following steps; measure the power of the signal (Ps), convert the given SNR in decibels (SNRdB)
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