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V A Mashin

Publications and source records attributed to V A Mashin.

5 recordsLinked to original sources
PubMed2004

[The functional state classification and evaluation of the stability level in mental loads based on the factor structure of heart rate variability parameters].

In the paper, outcomes of the researches devoted to factor analysis of heart rate variability parameters and definition of the most informative parameters for diagnostics of functional states and an evaluation of level of stability to mental loads, are presented. The factor structure of parameters, which unclude integral level of heart rate variability (1), balance between activity of vagus and brain cortical-limbic systems (2), integrated level of cardiovascular system functioning (3), is substantiated. Factor analysis outcomes have been used for construction of functional state classification, for their differential diagnostics, and for development and check of algorithm for evaluation of the stability level in mental loads.

Adult↗
PubMed2002

[Dependency of characteristics of heart rate variability on the average value of the R--R-intervals].

By the means of spectral analysis, dependency of heart rate variability (HRV) on average R--R-intervals (R--Rav, sec) is explored at controlled (forced) breathing. According to our findings, the dependency of the peak frequency at a spectral density graph for source series of R--R-intervals upon the RRav may be presented by the following formula: fp 1.0 = fr: RRav, where fp 1.0--peak frequency when R--Rav = 1.0 sec, fp--peak frequency at current R--Rav. For correcting (standardization) the frequency domain borders of spectral power (fd) of sources series of the R--Rav-intervals it is possible to use the formula: fd = fd 1.0 R--Rav, where fd 1.0--frequency domain border at R--Rav = 1.0 sec. The correction (standardization) of frequency domain borders of spectral power (fd), frequency peaks (fp 1.0) of sources series of the R--Rav-intervals as compared to current R--Rav allows to compare different series of the R--Rav-intervals without using the transformation to the discrete event series (DES).

Adult↗
PubMedDate not supplied

[Connection of the tangents of the regression slope of the heart rate graph with linear and nonlinear dynamics in stationary short-time series].

The connection of the regression slope of heart rate graph (b1) with linear and nonlinear dynamics in stationary short-time series (256 points) was studied. A new index for the estimation of nonlinear dynamics in stationary short-time series was used, which is based on the correlation dimension. The results of the study indicated that the dynamics of heart rate in stationary short-time series can be represented as the sum of linear (periodic) and nonlinear (stochastic) processes. A relation of b1 with both linear and nonlinear dynamics of heart rate was found. The formulas for the calculation of absolute and relative (to the amplitude of periodic fluctuations) noise levels in heart rate dynamics were derived. A comparative analysis of nonlinear dynamics of heart rate in stationary short-time series for different functional states of humans was performed. The increase in the relative noise level in heart rate dynamics with increasing breathing frequency is related not only to a decrease in control breathing amplitude but also to an increase in the noise amplitude. The decrease in the absolute noise level for nervous excitation, fatigue, and mental stress were found. The predominance of nonlinear (stochastic) processes over linear (periodic) processes in the relaxed state was established.

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