ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


For citation:

Nikulina M. V., Antonets V. A. Experience in assessing heart rate variability by smoothed cardiointervalograms. Izvestiya VUZ. Applied Nonlinear Dynamics, 2022, vol. 30, iss. 2, pp. 176-188. DOI: 10.18500/0869-6632-2022-30-2-176-188

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
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Language: 
Russian
Article type: 
Article
UDC: 
612.176:4, 004.932

Experience in assessing heart rate variability by smoothed cardiointervalograms

Autors: 
Nikulina Marina Valentinovna, Lobachevsky State University of Nizhny Novgorod
Antonets Vladimir Aleksandrovich, Institute of Applied Physics of the Russian Academy of Sciences
Abstract: 

The objective of this study is to show the possibility of using the smoothing cardiointervalograms (CIG) method which is solely time domain analysis of CIG to separate and display the influence of various mechanisms of human physiological regulation systems on his heart rate. Methods.This paper shows the possibility of using the method of smoothing the cardiointervalogram by means of a moving average for its subsequent decomposition into slow and fast components. Decomposition results are visualized by line graphs and pseudo-phase portraits. Visualization settings allow us to isolate unique transients and calculate its timing. The method is applied to data obtained under different subject functional states and differing in the level of adaptation risks, the presence or absence of stress. For analysis were selected stress episodes detected using the information and telecommunication technology of event-related cardiac telemetry (ITT ERCT) presented by the Internet resource “StressMonitor”. Results.For the numerical series of RR-intervals, a clear division into fast and slow components is obtained. An algorithm for identifying the frequency content of heart rate variability has been formulated and tested. A visualization method is proposed that is convenient for comparing data obtained for different patients. A pseudo-phase portrait pattern corresponding to the moment of stress onset is found. The proposed method reduced the discreteness of identifying the stress onset moment from 10 seconds to single heart beats. Conclusion. The correspondence of the results to the verified ITT ERCT method and the Baevsky–Chernikova concept of adaptive risk has been demonstrated. This confirms the possibility of using the time cardiointervalograms smoothing method for the analysis of heart rate variability.

Acknowledgments: 
The authors thank S. A. Polevaya, Head of the Department of Psychophysiology, Lobachevsky University of Nizhny Novgorod for the opportunity to use the Internet resource “StressMonitor”.
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Received: 
15.11.2021
Accepted: 
07.02.2022
Published: 
31.03.2022