L.Yu. Krivonogov1, S.I. Gerashchenko2, D.V. Papshev3, P.D. Kryanina4, E.S. Khalyapina5

1–5 Penza State University (Penza, Russia)
1 leonidkrivonogov@yandex.ru, 2 mpo@list.ru, 3 rover_d@mail.ru, 4 kryanina.lia@yandex.ru, 5 evgenia.halyapina@yandex.ru

The development of modern medical technologies is inextricably linked with the improvement of methods and tools for recording, measuring, processing, and analyzing biomedical signals (BMS). One of the main problems that makes it difficult to extract complete and reliable information from the BMS is the presence of various interferences. Interference is the main source of measurement uncertainties, complicates the analysis of BMS and can lead to inaccurate and even erroneous diagnostic conclusions. In this regard, when developing medical diagnostic systems, it is necessary to use various methods for suppressing interference in the BMS. In general, BMS are non-stationary and nonlinear, with a time-varying spectral composition, and the spectra of the useful signal and interference are usually significantly overlapping. To suppress interference in such signals, most existing filtering methods are not effective enough, as they significantly distort the informative sections of the BMS, reducing the effectiveness of medical diagnostics.

The aim of the study is to develop algorithms for interference suppression in BMS, which ensure significant interference suppression with minimal distortion of useful signals. To achieve this goal, the following research objectives were solved: the possibility of effective suppression of interference in BMS based on methods of decomposition of complex signals into narrow-band components was substantiated and a decomposition method adapted to the non-stationary nature of signals was selected; specialized algorithms have been created to suppress high-frequency and low-frequency interference in the BMS; their quality was assessed.

The use of developed algorithms for suppressing interference in the BMS are the basis for creating a new generation of cardiac diagnostic systems that provide high-precision measurement of parameters and identification of diagnostically important changes in the BMS, and can increase the reliability of diagnostics of the cardiovascular system.

Krivonogov L.Yu., Gerashchenko S.I., Papshev D.V., Kryanina P.D., Khalyapina E.S. Interference suppression algorithms in biomedical signals based on modified empirical mode decomposition. Biomedicine Radioengineering. 2025. V. 28. № 5. P. 23–26. DOI: https:// doi.org/10.18127/j15604136-202505-05 (In Russian)

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