Skip to main content
Log in

Application of Joint Recurrence Analysis for Estimating Phase Synchronization of Physiological Signals

  • Published:
Technical Physics Aims and scope Submit manuscript

Abstract

The joint recurrence analysis is used to reveal differences in the phase synchronization between intermittent photic stimulation and brain responses of patients with cardiac fibrillation of paroxysmal and persistent types. As a measure of phase synchronization between two signals, we consider the mutual correlation factor between recurrence probabilities of corresponding phase trajectories. The value of this coefficient increases upon an increase in the cardiac fibrillation time and in the extent of decline of cognitive functions for brain responses to theta-range frequencies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.

Similar content being viewed by others

REFERENCES

  1. E. Lowet, M. J. Roberts, P. Bonizzi, J. Karel, and P. De Veerd, PLoS One 11, 1 (2016). https://doi.org/10.1371/journal.pone.0146443

    Article  Google Scholar 

  2. B. Kralemann, M. Fruhwirth, A. Pikovsky, M. Rosenblum, Th. Kenner, J. Schaefer, and M. Moser, Nat. Commun. 4, 2418 (2013). https://doi.org/10.1038/ncomms3418

    Article  ADS  Google Scholar 

  3. A. E. Hramov, A. A. Koronovskii, V. I. Ponomarenko, and M. D. Prokhorov, Phys. Rev. E 73, 026208 (2006). https://doi.org/10.1103/PhysRevE.73.026208

  4. A. B. Bespyatov, M. B. Bodrov, V. I. Gridnev, V. I. Ponomarenko, and M. D. Prokhorov, Nonlinear Phenom. Complex Syst. 6 (4), 885 (2003).

    Google Scholar 

  5. M. C. Romano, M. Thiel, J. Kurths, I. Z. Kiss, and J. L. Hudson, Europhys. Lett. 71 (3), 466 (2005).

    Article  ADS  Google Scholar 

  6. J. Kurths, M. C. Romano, M. Thiel, G. V. Osipov, M. V. Ivanchenko, I. Z. Kiss, and J. L. Hudson, Nonlinear Dyn. 44, 135 (2006).

    Article  Google Scholar 

  7. D. Rangaprakash and N. Pradhan, Biomed. Signal Process. Control 11, 114 (2014).

    Article  Google Scholar 

  8. M. Acciarresi, M. Paciaroni, G. Agnelli, N. Falocci, V. Caso, C. Beccatini, S. Marcheselli, C. Rueckert, A. Pezzini, A. Morotti, P. Costa, A. Padovani, L. Csiba, L. Szabó, S.-I. Sohn, et al., J. Stroke Cerebrovasc. Dis. 26, 1363 (2017).

    Article  Google Scholar 

  9. A. Singh-Manoux, A. Fayosse, S. Sabia, M. Canonoco, M. Bobak, A. Elbaz, M. Kivimäki, and A. Dugravot, Eur. Heart J. 38, 2612 (2017).

    Article  Google Scholar 

  10. E. Z. Goluchova, M. V. Shumilina, and A. K. Kabisova, Kreativ. Kardiol. 12, 31 (2018). https://doi.org/10.24022/1997-3187-2018-12-1-31-39

    Article  Google Scholar 

  11. O. E. Dik and A. L. Glazov, Tech. Phys. 66, 560 (2021). https://doi.org/10.1134/S1063784221040058

    Article  Google Scholar 

  12. N. Marwan, M. C. Romano, M. Thiel, and J. Kurths, Phys. Rep. 438, 237 (2007). https://doi.org/10.1016/j.physrep.2006.11.001

    Article  ADS  MathSciNet  Google Scholar 

  13. F. Takens, in Dynamical Systems and Turbulence (Lecture Notes in Mathematics), Ed. by D. Rand and L.-S. Young (Springer, Berlin, 1981). https://doi.org/10.1007/BFb0091903

    Book  Google Scholar 

  14. A. M. Fraser and H. L. Swinney, Phys. Rev. 33, 1134 (1986).

    Article  ADS  MathSciNet  Google Scholar 

  15. M. B. Kennel, R. Brown, and H. D. Abarbanel, Phys. Rev. A 45, 3403 (1992).

    Article  ADS  Google Scholar 

  16. Y. Hochberg and A. C. Tamhane, Multiple Comparison Procedures (Wiley, Hoboken, NJ, 1987).

    Book  Google Scholar 

  17. L. Kocarev and U. Parlitz, Phys. Rev. Lett. 76, 1816 (1996).

    Article  ADS  Google Scholar 

  18. M. C. Romano, M. Thiel, J. Kurths, and C. Grebogi, Phys. Rev. E 76, 036211 (2007).

  19. O. E. Dick, I. A. Svyatogor, A. D. Nozdrachev, and N. L. Guseva, Hum. Physiol. 45, 40 (2019). https://doi.org/10.1134/S0362119719010055

    Article  Google Scholar 

  20. A. I. Fedotchev, A. T. Bondar, S. G. Matrusov, V. S. Semenov, and A. G. Soin, Usp. Fiziol. Nauk 37 (4), 82 (2006). https://www.elibrary.ru/item.asp?id=9296116

    Google Scholar 

  21. O. E. Dick and I. A. Svyatogor, Neurocomputing 165, 361 (2015). https://doi.org/10.1016/j.neucom.2015.03.025

    Article  Google Scholar 

Download references

ACKNOWLEDGMENTS

The authors are grateful to N.L. Guseva for provision of experimental EEG patterns.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to O. E. Dick or A. L. Glazov.

Ethics declarations

The authors declare that there is no conflicts of interest.

Additional information

Translated by N. Wadhwa

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dick, O.E., Glazov, A.L. Application of Joint Recurrence Analysis for Estimating Phase Synchronization of Physiological Signals. Tech. Phys. 67, 48–60 (2022). https://doi.org/10.1134/S1063784222010030

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1063784222010030

Keywords:

Navigation