Kotelnikov Institute of Radio Engineering and Electronics of RAS Русский Sign in Submit a paper
Journal of Radio Electronics Online scientific journal · eISSN 1684-1719
2019, № 5 · BIOMEDICAL RADIO ELECTRONICS

Time series analysis in self-regulating systems

V.F. Fedorov1,2,3,4

1 Московский физико-технический институт (государственный университет)
2 Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia
3 Российский университет дружбы народов, Moscow, Russia
4 Peoples' Friendship University of Russia, Russia
Full text (PDF) DOI: 10.30898/1684-1719.2019.5.9 EDN TXKCLP

Abstract

This paper describes a new approach to time series analysis of quantitative parameters of functional diagnostics signals. The normalization of measured values is introduced, which reduces the influence of individual differences when comparing data of different patients In addition, the normalization allows to build classification rules based on multivariate statistics and draw distinctions between heterogeneous groups more precisely. The effectiveness of normalization algorithms tested on the time series of durations of cardiac cycles, systolic output and peripheral vascular resistance. We suggest using this approach for time series analysis of quantitative parameters of other self-regulating systems.

  • self-regulating systems
  • time series analysis
  • functional diagnostics
Аннотация (на русском)

Анализ временных рядов в саморегулирующихся системах

В работе описан новый подход к анализу временных рядов количественных параметров сигналов функциональной диагностики. Введена нормализация измеренных значений, которая уменьшает влияние индивидуальных различий при сравнении данных разных пациентов. Кроме того, нормализация позволяет строить правила классификации на основе многомерной статистики и точнее проводить различия между разнородными группами. Эффективность алгоритмов нормализации проверена на временных рядах длительностей сердечных циклов, систолического выброса и периферического сосудистого сопротивления. Мы предлагаем использовать этот подход для анализа временных рядов количественных параметров других саморегулирующихся систем.

For citation

Fedorov V.F. Time series analysis in self-regulating systems // Journal of Radio Electronics. – 2019. – No. 5. https://doi.org/10.30898/1684-1719.2019.5.9

References

  1. Einthoven W. Galvanometrische registratie van het menschelijk electrocardiogram. Leiden: Eduard Ijdo, 1902. P. 101-107.
  2. All Nobel Prizes on Physiology and Medicine. Site of Nobel Prize Organization Available at https://www.nobelprize.org/nobel_prizes/medicine/laureates/1924/press.html (23.01.2018)
  3. Einthoven W. Le télécardiogramme. Paris: Arch Int Physiol, 1906. No 4. P. 132-164.
  4. Einbrod. Über den Einfluß der Atembewegung auf Herzschlag und Blutdruck. Sber. Akad. Wiss. Wien; Math. Nat. Kl., 2. Abt., 40 (1860), S. 361-418.
  5. Hunt, R.J. Experiments on the relation of the inhibitory to the acceleration nerves of the heart. J.Exp. Med. 1897, No.2, 151 -179.
  6. Bainbridge, F.A. The influence of venous filling upon the rate of the heart. J. Physiol. (London), 1915, Vol.50. pp. 65.
  7. Bainbridge, F.A. The relation between respiration and pulse-rate. J. Physiol. (London), 1920, Vol. 54, pp. 192.
  8. Boas EP, Goldschmidt EF. eds. The Heart Rate. Charles C Thomas. Springfield, Illinois, 1932.
  9. Brown, G.L. and Eccles, J.C., The action of a single vagal volley on the rhythm of the heart beat. J. Physiol., 1934, Vol. 82, pp. 211 -241.
  10. Rosenblueth, A. and Simeone, A.F., The interrelations of vagal and accelerator effects on cardiac rate. Amer. J. Physiol., 1934, Vol. 11, pp. 42-45.
  11. Malmo RB, Shagass C. The variability of heart rate in relation to age, sex, and stress. J Appl Psychol., 1949, No. 2, p. 181-184.
  12. Gol'dman L.N., i Merkul' V.E. Universal deviometer and the value of deviometry in assessing the functional state of the myocardium. Klinicheskaya meditsina -Clinical Medicine, 1951, No. 1, p. 80.
  13. Warner H.R., Cox A. Mathematical model of heart rate control by sympathetic and vagus efferent information. J. Appl. Physiol., 1962, No. 17, p. 349 -355.
  14. Hon E.H.; Lee S.T. Electronic evaluation of the fetal heart rate. American Joumal of Obstetlics and Gynecology, 1965, Vol. 87, No. 6, pp. 81426.
  15. Parin V.V., Baevskij R.M., Volkov J.N., Gazenko O.G. -Leningrad, Medicina Publ., 1967, 206 p..
  16. Heart Rate Variability -Standards of Measurement, Physiological Interpretation, and Clinical Use, Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation, 1996, Vol. 93, 1043-1065.
  17. Schmidt-Nielsen K. Scaling: Why is Animal Size so Important? Cambridge University Press, 1984, 241 pp.
  18. Akhmadiev G.M. //Uchenye zapiski Kazanskoj gosudarstvennoj akademii veterinarnoj mediciny im. N.E. Baumana -Bulletin of Kazan State Academy of Ve terinary Medicine, 2016, Vol. 225, No. 1. pp. 3-7..
  19. Shlyk N.I., Baevskij R.M. Heart Rate and type of vegetative regulation in assessing the level of health of the population and the functional preparedness of athletes. Materials of the VI All-Russian Symposium. Izhevsk, Publishing Center «Udmurtskij universitet», 2016. 608 p..
  20. Dudnik E.N., Kalita A.V., Dibrova E.A., Fedorov S.M., Karimova I.M., Glazachev O.S., Sudakov K.V. Individual changes in the activity of the heart with the same physical effects in individuals with different tones of the autonomic nervous system. Bulletin of the Russian Academy of Medical Sciences, 2007, No. 3, pp. 39 -43..
  21. Ramalho ESV, Souza-Junior EL, Magnani M, Braga VA. Gender Differences in Heart Rate Variability Among Individuals Undergoing Regular Resistance Training Preliminary observations. Sultan Qaboos Univ Med J., 2017, Vol. 17, No.2, pp. e209-e212. Doi: 10.18295/squmj.2016.17.02.012.
  22. Rannelli LA1, MacRae JM1,2,3, Mann MC1,3, Ramesh S1,3, Hemmelgarn BR1,2,3,4, Rabi D1,3,4, Sola DY2,3, Ahmed SB1,2,3. Sex differences in associations between insulin resistance, heart rate variability, and arterial stiffness in healthy women and men: a physiology study. Can. J. Physiol. Pharmacol., 2017, Vol. 95, No. 4, pp. 349-355. Doi: 10.1139/cjpp-2016-0122.
  23. Vapnik V.N Algoritmi i programmy dlya vosstanovleniya zavisimostey . Moscow, Nauka Publ., 1984, p. 688..
  24. Fedorov V.F. Methodology of the analysis of the dynamics of the quantitative parameters of the functional diagnostics of the cardiovascular system. Doctoral thesis abstract. Moscow, 2014..