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Pathological discrimination of the phonocardiogram signal using the bispectral technique

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Abstract

Phonocardiography is a dynamic non-invasive and relatively low-cost technique used to monitor the state of the mechanical activity of the heart. The recordings generated by such a technique is called phonocardiogram (PCG) signals. When shown visually, PCG signals can provide more insights of heart sounds for medical doctors. Thus, several approaches have been proposed to analyse these sounds through PCG recordings. However, due to the complexity and the high nonlinear nature of these recordings, a computer-assisted technique based on higher-order statistics HOS is shown to be, among these techniques, an important tool in PCG signal processing. The third-order spectra technique is one of these techniques; known as bispectrum, it can provide significant information to support physicians with an accurate and objective interpretation of heart condition. This technique is implemented and discussed in this paper. The implemented technique is used for the analysis of heart severity on nine different PCG recordings. These are normal, innocent murmur, coarctation of the aorta, ejection click, atrial gallop, opening snap, aortic stenosis, drum rumble, and aortic regurgitation. A unique bispectrum representation is generated for each type of heart sounds signal. Then, based on the bispectrum analysis, fifteen higher-order spectra HOS features such as the bispectral amplitude, the entropies, the moments, and the weighted center are extracted from each PCG record. The obtained HOS-features showed a well-correlated evolution with the increasing importance of heart severity leading therefore to a high potential in discriminating pathological PCG signals. One should know that, generally, classification of pathological PCG signals refers to the distinction between the presence of a pathology from its absence (binary response) while the discrimination considered in this paper provides an analogue response (value) which can vary from one pathology to another in an increasing or decreasing way.

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Acknowledgements

The authors would like to thank the Directorate-General of Scientific Research and Technological Development (Direction Générale de la Recherche Scientifique et du Développement Technologique, DGRSDT, URL: www.dgrsdt.dz, Algeria) for the financial assistance through a monthly allowance provided to the doctoral students to do their research.

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No, I have nothing to report. This study was not funded by any party: it is an academic PhD study.

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Authors and Affiliations

  1. Biomedical Engineering Department, Faculty of Technology, Biomedical Engineering Laboratory (GBM), Tlemcen University, Tlemcen, BP 119, Algeria

    Sid Ahmed Berraih, Yettou Nour elhouda Baakek & Sidi Mohammed El Amine Debbal

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  1. Sid Ahmed Berraih
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  2. Yettou Nour elhouda Baakek
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  3. Sidi Mohammed El Amine Debbal
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All authors were involved in the work leading up to the manuscript. The results are appropriately placed in the context of prior and existing research. All sources used are properly disclosed (correct citation).

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Correspondence to Sidi Mohammed El Amine Debbal.

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Berraih, S.A., Baakek, Y.N.e. & Debbal, S.M.E.A. Pathological discrimination of the phonocardiogram signal using the bispectral technique. Phys Eng Sci Med 43, 1371–1385 (2020). https://doi.org/10.1007/s13246-020-00943-7

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  • DOI: https://doi.org/10.1007/s13246-020-00943-7

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