Izvestiya of Saratov University.


ISSN 1817-3020 (Print)
ISSN 2542-193X (Online)

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Kurbako A. V., Borovkova E. I., Kiselev A. R., Skazkina V. V., Ponomarenko V. I., Bezruchko B. P., Karavaev A. S. The method for diagnostics of the phase synchronization of the vegetative control of blood circulation in real time. Izvestiya of Saratov University. Physics , 2021, vol. 21, iss. 3, pp. 213-221. DOI: 10.18500/1817-3020-2021-21-3-213-221, EDN: YQGXIV

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The method for diagnostics of the phase synchronization of the vegetative control of blood circulation in real time

Kurbako Aleksandr Vasilievich, Saratov State University
Borovkova Ekaterina Igorevna, Saratov State University
Kiselev Anton Robertovich, Saratov State University
Skazkina Victoria Viktorovna, Saratov State University
Ponomarenko Vladimir Ivanovich, Saratov Branch of the Institute of RadioEngineering and Electronics of Russian Academy of Sciences
Bezruchko Boris Petrovich, Saratov State University
Karavaev Anatoly Sergeevich, Saratov State University

Background and Objectives: The development of methods for the analysis of non-stationary signals of biological nature makes it possible to solve a number of fundamental and applied problems. The use of these methods is promising for the diagnosis and prevention of diseases of the cardiovascular system. The creation of the device makes it possible to detect diseases at an early stage. However, this requires the development of methods for analyzing non-stationary signals of biological nature in real time. Therefore, the purpose of the study is the method for diagnosing the phase chain of autonomic control of blood circulation in real time. Materials and Methods: Test realizations of instantaneous phase differences were created, repeating the statistical properties of real data recorded from people. A comparison of the sensitivity of the developed and known methods for different values of the input parameters was carried out. The complexity of the two methods was estimated. Results: A method was developed for diagnosing the phase chains of autonomic control of blood circulation in real time. The methods showed similar sensitivity values. The developed method has less complexity in comparison with the known method. Conclusion: The developed method can be used to diagnose the phase synchronization of the autonomic regulation circuits of the heart and blood vessels in real time.

The reported study was funded by RFBR according to the research project No. 20-02-00702, and by the Grant Council of the President of the Russian Federation for the state support of young Russian scientists – candidates of sciences (project No. MK-2325.2021.1.2) and scientific schools (project No. NSH-2594.2020.2).
  1. Pikovsky A., Rosenblum M., Kurths J. Synchronization: A universal concept in nonlinear sciences. Cambridge, Cambridge University Press, 2001. 411 p.
  2. Blekhman I. I. Sinhronizatsiya dinamicheskih sistem [Synchronization of Dynamic Systems]. Moscow, Nauka Publ., 1971. 896 p. (in Russian).
  3. Meissimilly G., Rodriguez J., Rodriguez G., Gonzalez R., Caiiizares M. Microcontroller-Based Real-Time QRS Detector for Ambulatory Monitoring. Proceedings of the 25 Annual Intemational Conference of the IEEE EMBS, 2003, pp. 2881–2884.
  4. Onuiri E. E., Awodele O., Adeagbo B. O., Madu N. C., Johnson I. E. Design and construction of a microcontroller-based heartbeat monitoring device with display. International Journal of Engineering & Technology, 2014, vol. 3, iss. 2, pp. 279–289.
  5. ww1.microchip.com. Available at: https://www.google. com/urlsa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjm74a9h5vvAhVQlosKHaoiB2gQFjABegQIAxAD&url=http%3A%2F%2Fww1.microchip.com%2Fdownloads%2Fen%2Fdevicedoc%2F 30453b.pdf&usg=AOvVaw3R9nav33JGDNBf-YeXLxEt (accessed 4 March 2021).
  6. Karavaev A. S., Prokhorov M. D., Ponomarenko V. I., Kiselev A. R., Gridnev V. I., Ruban E. I., Bezruchko B. P. Synchronization of low-frequency oscillations in the human cardiovascular system. Chaos, 2009, vol. 19, pp. 033112. https://doi.org/10.1063/1.3187794
  7. Borovkova E. I., Karavaev A. S., Ponomarenko V. I., Prokhorov M. D. Comparison of methods for phase synchronization diagnostics from test data modeling nonstationary signals of biological nature. Izvestiya of Saratov University. Physics, 2015, vol. 15, iss. 3, pp. 36–42 (in Russia). https://doi.org/10.18500/1817- 3020-2015-15-3-36-42
  8. Maximilian R., Andreas W. Fixed Point Library According to ISO/IEC Standard DTR 18037 for Atmel AVR Processors. Wien, IEEE Press, 2007. 138 p.
  9. Borovkova E. I., Karavaev A. S., Kiselev A. R., Shvarts V. A., Mironov S. A., Ponomarenko V. I., Prokhorov M. D. Method for diagnostics of synchronization of 0.1 Hz rhythms of cardiovascular system autonomic regulation in real time. Annals of Arrhythmology, 2014, vol. 11, no. 2, pp. 129–136 (in Russian).
  10. Steven W. S. Digital Signal Processing. A Practical Guide for Engineers and Scientists. New York, Newnes, 2003. 650 p.
  11.  medicom-mtd.com. Available at: http://medicom-mtd. com/htm/Licen/sert_13_temp.html (accessed 4 March 2021) (in Russian).
  12. Baevsky R. M., Ivanov G. G., Chireikin L. V., Gavrilushkin A. P., Dovgalevskiy P. Ya., Kukushkin Yu. A., Mironova T. F., Prilutskiy D. A., Semenov A. V., Fedorov V. F., Fleyshman A. N., Medvedev M. M. Analysis of heart rate variability using various electrocardiographic systems (guidelines). Journal of Arrhythmology, 2001, vol. 24, pp. 66–85 (in Russian).
  13. Ayvazyan S. A., Enyukov I. S., Meshalkin L. D. Prikladnaya statistika: Osnovy modelirovaniya i pervichnaya obrabotka dannyh [Applied Statistics: Basics of Modeling and Primary Data Processing. Ed. by S. A. Ayvazyan]. Moscow, Financy i Statistika Publ., 1983. 471 p. (in Russian).
  14. Tehan P., Bray A., Keech R., Rounsley R., Carruthers A., Chuter V. H. Sensitivity and specificity of the toe brachial index for detecting peripheral arterial disease: initial findings. J. Ultrasound Med., 2015, vol. 34, pp. 1737–43. https://doi.org/10.7863/ultra.15.14.09071
  15. Sonter J., Tehan P., Chuter V. Toe brachial index measured by automated device compared to duplex ultrasonography for detecting peripheral arterial disease in older people. Vascular, 2017, vol. 25, iss. 6, pp. 612–617.
  16. Power M., Fell G., Wright M. Principles for high-quality, high-value testing. BMJ Evidence-Based Medicine, 2013, vol. 18, pp. 5–10.
  17. Aificher E. S., Jervis B. U. Digital Signal Processing: A Practical Approach. 2nd ed. Harlow, Prentice Hall, 2002. 933 p.