Development of an atrioventricular block prediction of method for portable heart monitoring system

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.258791

Keywords:

holter monitor, automatic conclusion, cardiovascular system, cardiovascular disease, life-threatening arrhythmia

Abstract

The object of the study is a portable system that allows real-time monitoring of the state of the heart for the timely provision of medical care. The task of detecting atrioventricular (AV) blocks in the conditions of free motor activity of the patient is being solved. To develop a method for detecting AV block, models of the electrical activity of the heart were used to take into account the spatiotemporal organization of the process of spreading excitation, analyze the dynamics of the behavior of the cardiovascular systems (CVS) for any value of the period of atrial excitation, and assess the degree of fitness of the CVS. The proposed method made it possible to determine the heart rate (HR) at which the development of AV block is possible. AV block of the III degree – heart rate 304 bpm; AV block of the II degree with the loss of half of the impulses – heart rate 260 bpm; AV block II degree with loss of individual impulses – heart rate 234 bpm; AV block of the 1st degree – heart rate 200 bpm. Prediction of AV block allows assessing the degree of “training” of the patient’s heart. The obtained quantitative results are consistent with the heart rate values known to modern health care. The developed method was implemented on the basis of a portable ECG monitoring system previously developed by the authors. Tests of the portable ECG monitoring system indicate an increase in the sensitivity and specificity of diagnosing cardiac arrhythmia and confirm the achievement of the goal of this study: improving the efficiency of diagnostics and expanding the functionality of the portable ECG monitoring system

Supporting Agency

  • The current model of a portable monitoring system was developed on the basis of Satbayev University under the grant program of the Science Fund of the Republic of Kazakhstan. Project No. 0281-18-«Portable ECG device».

Author Biographies

Ainur Bekbay, Satbayev University

Doctoral Student

Department of Robotics and Engineering Tools of Automation

Zhadyra Alimbayeva, Kazakh National Women’s Teacher Training University

Teacher

Department of Informatics and Applied Mathematics

Chingiz Alimbayev, Institute of Mechanics and Engineering named after U. A. Joldasbekov

PhD, Senior Researcher

Nurlan Bayanbay, Satbayev University

Doctoral Student, Senior Lecturer

Department of Robotics and Engineering Tools of Automation

Kassymbek Ozhikenov, Satbayev University

Candidate of Technical Sciences, Head of Department

Department of Robotics and Engineering Tools of Automation

Yerkat Mukazhanov, Zhetysu University

Candidate of Physical and Mathematical Sciences, Associate Professor

References

  1. Timmis, A., Vardas, P., Townsend, N., Torbica, A., Katus, H., De Smedt, D. et. al. (2022). European Society of Cardiology: cardiovascular disease statistics 2021. European Heart Journal, 43 (8), 716–799. doi: https://doi.org/10.1093/eurheartj/ehab892
  2. Opoku-Acheampong, A. A., Rosenkranz, R. R., Adhikari, K., Muturi, N., Logan, C., Kidd, T. (2021). Tools for Assessing Cardiovascular Disease Risk Factors in Underserved Young Adult Populations: A Systematic Review. International Journal of Environmental Research and Public Health, 18 (24), 13305. doi: https://doi.org/10.3390/ijerph182413305
  3. Holter, N. J. (1961). New Method for Heart Studies: Continuous electrocardiography of active subjects over long periods is now practical. Science, 134 (3486), 1214–1220. doi: https://doi.org/10.1126/science.134.3486.1214
  4. Chou, I.-C., Hsueh, H.-C., Lee, R.-G. (2009). Example for mobile ECG holter design using FMEA model. Biomedical Engineering: Applications, Basis and Communications, 21 (01), 61–70. doi: https://doi.org/10.4015/s101623720900109x
  5. Liu, S.-H., Huang, Y.-F., Chen, C.-R. (2014). The wireless holter ECG system based on Zigbee. 2014 IEEE International Conference on Systems, Man, and Cybernetics.
  6. Gabbouj, M., Kiranyaz, S., Malik, J., Zahid, M. U., Ince, T., Chowdhury, M. E. H. et. al. (2022). Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 1–12. doi: https://doi.org/10.1109/tnnls.2022.3158867
  7. Zbitnieva, V. O., Voloshyna, O. B., Balashova, I. V., Dukova, O. R., Lysyi, I. S. (2021). Incidence of cardiac arrhythmias in patients with COVID-19 infection according to 24-hour electrocardiogram monitoring, Zbitnieva V. O., and etc., Zaporozhye medical journal, 23 (6), 759–765. doi: https://doi.org/10.14739/2310-1210.2021.6.239243
  8. Basnet, B. K., Manandhar, K., Shrestha, R., Shrestha, S., Thapa, M. (2009). Electrocardiograph and Chest X-ray in Prediction of Left Ventricular Systolic Dysfunction. Journal of Nepal Medical Association, 48, 176. doi: https://doi.org/10.31729/jnma.343
  9. Katscher, U., Weiss, S. (2022). Mapping electric bulk conductivity in the human heart. Magnetic Resonance in Medicine, 87 (3), 1500–1506. doi: https://doi.org/10.1002/mrm.29067
  10. Aliev, R. R. (2010). Computer simulation of the electrical activity of the heart. Uspekhi fizicheskikh nauk, 41 (3), 44–63.
  11. Noble, D. (1962). A modification of the Hodgkin-Huxley equations applicable to Purkinje fibre action and pacemaker potentials. The Journal of Physiology, 160 (2), 317–352. doi: https://doi.org/10.1113/jphysiol.1962.sp006849
  12. Herve, D., Drouard Haelewyn, C., Rousselot, J. F. (2002). The A.B.C. of ECG. Pratique Medicale and Chirurgicale de l'Animal de Compagnie, 37 (6), 487–489.
  13. Simova, I., Predovski, M., Christov, I., Simov, D. (2017). Remote ECG Interpretation: Guidelines and their Implementation. 2017 Computing in Cardiology Conference (CinC). doi: https://doi.org/10.22489/cinc.2017.366-095
  14. Orlov, V. N. (2017). Rukovodstvo po elektrokardiografii. Moscow: 560. Available at: https://ivgma.ru/attachments/16530
  15. Pravdin, S. F., Epanchintsev, T. I., Nezlobinskii, T. V., Panfilov, A. V. (2020). Induced drift of scroll waves in the Aliev–Panfilov model and in an axisymmetric heart left ventricle. Russian Journal of Numerical Analysis and Mathematical Modelling, 35 (5), 273–283. doi: https://doi.org/10.1515/rnam-2020-0023
  16. Li, A., Stroik, D., Schaaf, T., Yuen, S., Kleinboehl, E., Cornea, R. L., Thomas, D. D. (2020). Biophysics of the SERCA2A/DWORF Complex, Implications for Treatment of Heart Failure. Biophysical Journal, 118 (3), 593a. doi: https://doi.org/10.1016/j.bpj.2019.11.3210
  17. Von Rosenberg, W., Hoting, M.-O., Mandic, D. P. (2019). A physiology based model of heart rate variability. Biomedical Engineering Letters, 9 (4), 425–434. doi: https://doi.org/10.1007/s13534-019-00124-w
  18. Stenzinger, R. V., Tragtenberg, M. H. R. (2022). Cardiac reentry modeled by spatiotemporal chaos in a coupled map lattice. The European Physical Journal Special Topics, 231 (5), 847–858. doi: https://doi.org/10.1140/epjs/s11734-022-00473-1
  19. Alimbayev, C., Alimbayeva, Z., Ozhikenov, K., Bodin, O., Mukazhanov, Y. (2020). Development of measuring system for determining life-threatening cardiac arrhythmias in a patient’s free activity. Eastern-European Journal of Enterprise Technologies, 1 (9 (103)), 12–22. doi: https://doi.org/10.15587/1729-4061.2020.197079

Downloads

Published

2022-06-30

How to Cite

Bekbay, A., Alimbayeva, Z., Alimbayev, C., Bayanbay, N., Ozhikenov, K., & Mukazhanov, Y. (2022). Development of an atrioventricular block prediction of method for portable heart monitoring system . Eastern-European Journal of Enterprise Technologies, 3(5 (117), 15–27. https://doi.org/10.15587/1729-4061.2022.258791

Issue

Vol. 3 No. 5 (117) (2022): Applied physics

Section

Applied physics

License

Copyright (c) 2022 Ainur Bekbay, Zhadyra Alimbayeva, Chingiz Alimbayev, Nurlan Bayanbay, Kassymbek Ozhikenov, Yerkat Mukazhanov

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.