Keywords: phonocardiogram, cardiointervalogram, heart sound segmentation, heart rate, signal processing
The algorithm for pulse measurement using a human’s and fetus’s phonocardiogram without classifying heart sounds
UDC 004.421
DOI: 10.26102/2310-6018/2022.36.1.018
The relevance of the research is due to the prospects of phonocardiogram employment for daily monitoring of a fetus’s and mother’s state by designing inexpensive portable devices. Currently, there are no software and hardware systems that completely solve this problem. In this regard, the article presents the algorithm for pulse measurement by means of a phonocardiogram for signal processing in the streaming mode. The algorithm feature is a human’s and fetus’s pulse measurement based on the heart sound segmentation without classifying them into the first and second heart sounds, as well as detecting them under the conditions of other physiological and mechanical sounds, absence of one of the heart sounds in the signal, and deviations in the segmented sound boundaries from the actual localization of the cardiovascular system. For assessing the credibility of the results, the pulse values, obtained by the developed algorithm and reference methods, were compared. The pulse values, calculated by two experts with the aid of a phonocardiogram, were used as a standard for comparison. The average relative deviation between the findings and the reference method results does not exceed 3 %. The article materials are of practical value for the design of a fetus and human state daily monitoring systems.
1. Healthcare in Russia. 2019. Moscow, Rosstat = Russian Federal State Statistics Service; 2019. 170 p. (In Russ.)
2. Kovacs F., Torok M., Habermajer I. A rule-based phonocardiographic method for long-term fetal heart rate monitoring. IEEE Transactions on Biomedical Engineering. 2000;47(1):124–130. DOI: 10.1109/10.817627.
3. Liu C., Springer D., Li Q., Moody B., Juan R.A., Chorro F.J., Clifford G. D. An open access database for the evaluation of heart sound algorithms. Physiological Measurement. 2016;37(12):2181–2213. DOI: 10.1088/0967-3334/37/12/2181.
4. Chetlur Adithya P., Sankar R., Moreno W.A., Hart S. Trends in fetal monitoring through phonocardiography: Challenges and future directions. Biomedical Signal Processing and Control. 2017;33:289–305. DOI: 10.1016/j.bspc.2016.11.007.
5. El-Segaier M., Lilja O., Lukkarinen S., Sörnmo L., Sepponen R., Pesonen E. Computer-Based Detection and Analysis of Heart Sound and Murmur. Annals of Biomedical Engineering. 2005;33(7):937–942. DOI: 10.1007/s10439-005-4053-3.
6. Tang H., Li T., Qiu T., Park Y. Fetal Heart Rate Monitoring from Phonocardiograph Signal Using Repetition Frequency of Heart Sounds. Journal of Electrical and Computer Engineering. 2016:1–6. DOI: 10.1155/2016/2404267.
7. Nivitha Varghees V., Ramachandran K.I., Soman K.P. Wavelet-based fundamental heart sound recognition method using morphological and interval features. Healthcare Technology Letters. 2018;5(3):81–87. DOI: 10.1049/htl.2016.0109. (In Russ.)
8. Tvardovskii V.I., Dmitrachkov V.V., Bylinskii N.N., Volkova O.N., Kaleda A.G., Nazarenko O.N., Samokhval O.V. Fundamentals of pediatric electrocardiography. Teaching aid. Minsk: Bashkirskii gosudarstvennyi meditsinskii universitet = Bashkir State Medical University; 2011. 76 p. (In Russ.)
9. Aed V.M., Isakov R.V., Sushkova L.T., Al'-Khaidri V.A. Algorithm of forming cardiontervalogram based on phonocardiogram. Radiotekhnicheskie i telekommunikatsionnye sistemy = Radio and telecommunication systems. 2016;22(2):34–43. (In Russ.)
10. International Standard. ISO 5840-2:2015 (E): Cardiovascular implants: cardiac valve prostheses. Part 2: Surgically implanted heart valve substitutes; 2015. URL: https://www.iso.org/standard/51314.html (accessed on: 1.12.2021).
11. Chung C.S., Karamanoglu M., Kovács S.J. Duration of diastole and its phases as a function of heart rate during supine bicycle exercise. American Journal of Physiology-Heart and Circulatory Physiology. 2004;287(5):H2003–H2008. DOI: 10.1152/ajpheart.00404.200.
12. Yuenyong S., Nishihara A., Kongprawechnon W., Tungpimolrut K. A framework for automatic heart sound analysis without segmentation. BioMedical Engineering OnLine, 2011;10(1):13. DOI:10.1186/1475-925x-10-13.
13. Kosteley Y.V., Zhdanov D.S., Borovskoy I.G. Non-local averaging filter adaptation for heart sounds amplification on fetus and humans’ phonocardiograms. Vestnik SibGUTI. 2021;3:77–91. (In Russ.)
14. Shargaeva N.V. Diagnostic of fetus’ threatening conditions during pregnancy and in delivery. Problemy zdorov'ya i ekologii = Health and Ecology Issues. 2005;3:103–112. (In Russ.)
15. Dares G.S., Houghton C.R.S., Redman C.W.G. Baseline in human fetal heart-rate records. BJOG: An International Journal of Obstetrics and Gynaecology. 1982;89(4):270–275. DOI: 10.1111/j.1471-0528.1982.tb04695.x.
16. Kazemnejad A., Gordany P., Sameni R. An open-access simultaneous electrocardiogram and phonocardiogram database, 2021. BioRxiv. DOI: 10.1101/2021.05.17.444563 (accessed on: 1.12.2021).
Keywords: phonocardiogram, cardiointervalogram, heart sound segmentation, heart rate, signal processing
For citation: Kosteley Y.V., Zhdanov D.S., Borovskoy I.G. The algorithm for pulse measurement using a human’s and fetus’s phonocardiogram without classifying heart sounds. Modeling, Optimization and Information Technology. 2022;10(1). URL: https://moitvivt.ru/ru/journal/pdf?id=1135 DOI: 10.26102/2310-6018/2022.36.1.018 (In Russ).
Received 24.01.2022
Revised 19.02.2022
Accepted 28.02.2022
Published 31.03.2022