L.V. Labunets1, M.Yu. Ryakhina2

1,2 Bauman Moscow State Technical University (Moscow, Russia)
1 labunets@bmstu.ru, 2 ryakhinamyu@bmstu.ru

The article is devoted to the actual problem of studying the indicators of instantaneous frequencies and periods of the pulse wave signal registered by electrocardiography and remote photoplethysmography and considering the indicators of heart rate variability on the basis of the obtained data.

Target – justification of the stages of the system approach to the automated analysis of remote photoplethysmography signals and the possibility of calculating heart rate variability indices by non-contact methods.

The basic indices of heart rate variability were obtained on the basis of rhythmograms. The obtained results were analysed on the correspondence between the values of instantaneous heart rate on the basis of remote photoplethysmography and electrocardiography data was carried out.

According to the price/quality criteria, the advantages of the methodology of structural decomposition of non-stationary time series of electrocardiography and remote photoplethysmography on their own wave processes were demonstrated. The effectiveness of machine learning methods for models of patterns hidden in the dynamics of the pulse wave for the identification of instantaneous periods of the basic heart rate tone of the subjects is substantiated.

Labunets L.V., Ryakhina M.Yu. Study of pulse wave parameters based on the instantaneous frequency of the remote photoplethysmography signal. Dynamics of complex systems. 2025. V. 19. № 3. P. 74−81. DOI: 10.18127/j19997493-202503-08 (in Russian).

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2. Labunets L.V., Borzov A.B., Makarova N.Yu. Intellectual Analysis of Pulse Wave Characteristics by Methods of Structural Decomposition of Photoplethysmography Signals. Journal of Communications Technology and Electronics. 2022. V. 67. № 2. P. 182–192. DOI 10.1134/S1064226922020097.
3. Labunets L.V., Ryakhina M.Yu. Sliding spectral correlation analysis of non-contact photoplethysmography signals for assessment of heart rate. Biomedical Engineering. 2023. V. 57. P. 265–270. DOI 10.1007/s10527-023-10312-9.
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