Mohammad Mehdi Movahedi - Department of Medical Physics and Biomedical Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
Mohamadreza Shakerpour - School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
Shahrokh Mousavi - Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
Ahmad Nori - Novin Iran Specialized Clinic, Shiraz, Iran
Seyyed Hesam Mousavian Dehkordi - Faculty of Electrical Engineering, Shiraz University of Technology, Shiraz, Iran
Hossein Parsaei - Department of Medical Physics and Biomedical Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

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 (S۱ and S۲) 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 ۱۵ healthy adults were acquired and analyzed using the developed system. The average accuracy of the system in correctly detecting the heart sounds was ۹۵.۶% for S۱ and ۹۳.۴% for S۲.  Conclusion: The presented system is cost-effective, user-friendly, and accurate in identifying S۱ and S۲ in PCG signals. Therefore, it might be effective in quantitative PCG and diagnosing heart diseases.

Electrocardiogram, Electrocardiography, Heart Sounds, Markov Chains, Phonocardiography, PCG Segmentation