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. 2023 Jun 1;13(3):261-268.
doi: 10.31661/jbpe.v0i0.2104-1301. eCollection 2023 Jun.

A Hardware-Software System for Accurate Segmentation of Phonocardiogram Signal

Affiliations

A Hardware-Software System for Accurate Segmentation of Phonocardiogram Signal

Mohammad Mehdi Movahedi et al. J Biomed Phys Eng. .

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.

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.

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.

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.

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.

Keywords: Electrocardiogram; Electrocardiography; Heart Sounds; Markov Chains; PCG Segmentation; Phonocardiography.

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Conflict of interest statement

None

Figures

Figure 1
Figure 1
Block diagram of the hardware system.
Figure 2
Figure 2
Block diagram of the proposed segmentation algorithm.
Figure 3
Figure 3
Original and de-noised electrocardiogram (ECG) and phonocardiogram (PCG) signals.

References

    1. Rangayyan RM, Lehner RJ. Phonocardiogram signal analysis: a review. Crit Rev Biomed Eng. 1987;15(3):211–36. - PubMed
    1. Springer DB, Tarassenko L, Clifford GD. Logistic regression-HSMM-based heart sound segmentation. IEEE Trans Biomed Eng. 2016;63(4):822–32. doi: 10.1109/TBME.2015.2475278. - DOI - PubMed
    1. Leatham A. Auscultation of the Heart and Phonocardiography. Churchill London; 1975.
    1. Castro A, Vinhoza TT, Mattos SS, Coimbra MT. Heart sound segmentation of pediatric auscultations using wavelet analysis. Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:3909–12. doi: 10.1109/EMBC.2013.6610399. - DOI - PubMed
    1. Huiying L, Sakari L, Iiro H. A heart sound segmentation algorithm using wavelet decomposition and reconstruction. Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ‘Magnificent Milestones and Emerging Opportunities in Medical Engineering’ (Cat. No.97CH36136); Chicago, IL, USA: IEEE; 1997. - DOI

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