https://doi.org/10.1140/epjs/s11734-022-00731-2
Regular Article
Problem of power spectra estimation in application to the analysis of heart rate variability
1
Institute of Physics, Saratov State University, 83 Astrakhanskaya St., 410012, Saratov, Russia
2
Laboratory of Modelling in Nonlinear Dynamics, Saratov Branch of the Institute of Radio Engineering and Electronics of Russian Academy of Sciences, 38 Zelyonaya St., 410019, Saratov, Russia
3
Research Institute of Cardiology, Saratov State Medical University, 112 Bolshaya Kazachya St., 410012, Saratov, Russia
4
Coordinating Center for Fundamental Research, National Medical Research Center for Therapy and Preventive Medicine, 10 Petroverigsky Per., 101990, Moscow, Russia
Received:
9
October
2022
Accepted:
28
November
2022
Published online:
4
January
2023
We investigated how the parameters of the spectral analysis affect standard deviation and error of the estimation of well-known indices for the heart rate variability. We compared the nonparametric Fourier transform to the parametric approach based on autoregressive models. We also investigated how the precision of the indices estimation depends on the choice of the window function, parameterization of the Bartlett’s method, and the lengths of time series. For each set of parameters, we calculated the sensitivity and specificity of the resulting indices when diagnosing arterial hypertension. To isolate and investigate the errors caused by inaccuracy of the spectral analysis itself, we conducted our study using the mathematical models of heart rate variability for healthy subjects and arterial hypertension patients, for which the correct values of the spectral indices are known. The obtained results suggest that the analysis of 20-min signals, comparing to 5-min signals, significantly decreases the standard deviation of the estimations and increases both their sensitivity and specificity. We found no advantages of using the parametric approach over the Fourier transform. We have shown that application of the Hann’s window function and normalization of the spectral indices decreases the sensitivity and specificity of the medical diagnostics.
Vladimir I. Gridnev, Vladimir I. Ponomarenko, Dmitry M. Ezhov, Mikhail D. Prokhorov, Anton R. Kiselev, Anatoly S. Karavaev contributed equally to this work.
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