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Front Bioeng Biotechnol. 2017 Sep 08;5:49. doi: 10.3389/fbioe.2017.00049. eCollection 2017.

Fetal Heart Sounds Detection Using Wavelet Transform and Fractal Dimension.

Frontiers in bioengineering and biotechnology

Elisavet Koutsiana, Leontios J Hadjileontiadis, Ioanna Chouvarda, Ahsan H Khandoker

Affiliations

  1. Laboratory of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  2. Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  3. Department of Electrical and Computer Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
  4. Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.

PMID: 28944222 PMCID: PMC5596097 DOI: 10.3389/fbioe.2017.00049

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.

Keywords: fetal heart rate; fetal heart sound; fetal phonocardiogram; fractal dimension thresholding; wavelet transform

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