Preliminary study in the analysis of the severity of cardiac pathologies using the higher-order spectra on the heart-beats signals

Author:

Berraih Sid Ahmed1,Baakek Yettou Nour Elhouda1,Debbal Sidi Mohammed El Amine1

Affiliation:

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

Abstract

Abstract Phonocardiography is a technique for recording and interpreting the mechanical activity of the heart. The recordings generated by such a technique are called phonocardiograms (PCG). The PCG signals are acoustic waves revealing a wealth of clinical information about cardiac health. They enable doctors to better understand heart sounds when presented visually. Hence, multiple approaches have been proposed to analyze heart sounds based on PCG recordings. Due to the complexity and the high nonlinear nature of these signals, a computer-aided technique based on higher-order statistics (HOS) is employed, it is known to be an important tool since it takes into account the non-linearity of the PCG signals. This method also known as the bispectrum technique, can provide significant information to enhance the diagnosis for an accurate and objective interpretation of heart condition. The objective expected by this paper is to test in a preliminary way the parameters which can make it possible to establish a discrimination between the various signals of different pathologies and to characterize the cardiac abnormalities. This preliminary study will be done on a reduced sample (nine signals) before applying it subsequently to a larger sample. This work examines the effectiveness of using the bispectrum technique in the analysis of the pathological severity of different PCG signals. The presented approach showed that HOS technique has a good potential for pathological discrimination of various PCG signals.

Publisher

Walter de Gruyter GmbH

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Bispectral analysis and information fusion technique for bearing fault classification;Measurement Science and Technology;2023-10-17

2. Heart Sounds Classification Based on High‐Order Spectrogram and Multi‐Convolutional Neural Network after a New Screening Strategy;Advanced Theory and Simulations;2023-10-13

3. ENTROPY PARAMETER OF CARDIAC DEGREE SEVERITY ANALYSIS;Journal of Mechanics in Medicine and Biology;2023-07-25

4. Differentiating of Respiratory Noises Based on Higher Order Spectral Analysis;2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO);2022-10-10

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