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JOURNALS // Izvestiya of Saratov University. Physics // Archive

Izv. Sarat. Univ. Physics, 2023 Volume 23, Issue 2, Pages 128–140 (Mi isuph482)

Biophysics and Medical Physics

Assessment of spatiotemporal heterogeneity of two-dimensional images on the example of photoplethysmograpic imaging of hemodynamics

A. A. Sagaidachnyi, I. Yu. Volkov, M. O. Tsoy, A. V. Fomin, D. I. Mayskov, A. Antonov, I. S. Zaletov, An. V. Skripal

Saratov State University

Abstract: Background and Objectives: The problem of representation of multidimensional data on a two-dimensional plane arises during the processing of a series of two-dimensional images in the spatiotemporal and time-frequency domains. When implementing time-frequency analysis, each point of the object is characterized by a function of two arguments, therefore, to visualize the results on a two-dimensional plane, it is necessary to reduce the data dimension. Materials and Methods: This paper describes a method for color coding the correlation of spectral features at each point of a two-dimensional dynamic image. The novelty of the proposed method in the using of the wavelet correlation function of the reference area with all other regions of interest of the object. In this case, the correlation value is color-coded and forms a correlation map in each of the analyzed spectral ranges. Results: This allows to select areas that have similar time-frequency spectra of investigated characteristics of the object. The application of the method is considered on the example of the analysis of the microhemodynamics of the human hand using photoplethysmographic imaging. The analysis was carried out in the spectral range (0.005-2 Hz), covering both cardiac and low-frequency hemodynamic oscillations of the respiratory, myogenic, neurogenic, and endothelial ranges. In general, there is a tendency to a decrease of correlation of the spectrum with distance from the reference area and with a decrease in the analyzed signal frequency. It is shown that photoplethysmographic signals recorded in the area of the distal phalanx of the finger are predominantly representative of cardiac oscillations in microhemodynamics of other areas of the hand (correlation of about 0.7) and less representative with respect to endothelial, neurogenic, myogenic and respiratory oscillations (correlation of about 0.4). Due to the established high spatial inhomogeneity of the spectral features, it is recommended to use several reference areas when using contact photoplethysmographic measurements. Conclusion: The considered method of visualizing the spatial correlation of spectral features can find practical application also in the field of hemodynamic analysis using laser Doppler, laser speckle contrast, thermographic or hyperspectral imaging.

Keywords: photoplethysmography, photoplethysmographic imaging, imaging photoplethysmography, wavelet, correlation, hemodynamics, microhemodynamics, spectral analysis.

UDC: 57.087.3:612.1

Received: 06.12.2022

DOI: 10.18500/1817-3020-2023-23-2-128-140



© Steklov Math. Inst. of RAS, 2024