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A Hardware-Software System for Accurate Segmentation of Phonocardiogram Signal.

Authors :
Movahedi MM
Shakerpour M
Mousavi S
Nori A
Mousavian Dehkordi SH
Parsaei H
Source :
Journal of biomedical physics & engineering [J Biomed Phys Eng] 2023 Jun 01; Vol. 13 (3), pp. 261-268. Date of Electronic Publication: 2023 Jun 01 (Print Publication: 2023).
Publication Year :
2023

Abstract

Background: Phonocardiogram (PCG) signal provides valuable information for diagnosing heart diseases. However, its applications in quantitative analyses of heart function are limited because the interpretation of this signal is difficult. A key step in quantitative PCG is the identification of the first and second sounds (S1 and S2) in this signal.<br />Objective: This study aims to develop a hardware-software system for synchronized acquisition of two signals electrocardiogram (ECG) and PCG and to segment the recorded PCG signal via the information provided in the acquired ECG signal.<br />Material and Methods: In this analytical study, we developed a hardware-software system for real-time identification of the first and second heart sounds in the PCG signal. A portable device to capture synchronized ECG and PCG signals was developed. Wavelet de-noising technique was used to remove noise from the signal. Finally, by fusing the information provided by the ECG signal (R-peaks and T-end) into a hidden Markov model (HMM), the first and second heart sounds were identified in the PCG signal.<br />Results: ECG and PCG signals from 15 healthy adults were acquired and analyzed using the developed system. The average accuracy of the system in correctly detecting the heart sounds was 95.6% for S1 and 93.4% for S2.<br />Conclusion: The presented system is cost-effective, user-friendly, and accurate in identifying S1 and S2 in PCG signals. Therefore, it might be effective in quantitative PCG and diagnosing heart diseases.<br />Competing Interests: None<br /> (Copyright: © Journal of Biomedical Physics and Engineering.)

Details

Language :
English
ISSN :
2251-7200
Volume :
13
Issue :
3
Database :
MEDLINE
Journal :
Journal of biomedical physics & engineering
Publication Type :
Academic Journal
Accession number :
37312888
Full Text :
https://doi.org/10.31661/jbpe.v0i0.2104-1301