Event-related potential analysis of using Empirical Wavelet Transform

N.V. Myasnikova; L.A. Dolgikh; M.G. Myasnikova

doi:10.18127/j15604136-202601-14

Event-related potential analysis of using Empirical Wavelet Transform

N.V. Myasnikova¹, L.A. Dolgikh², M.G. Myasnikova³

research article UDC 616 Pages: 73-78 doi.org/10.18127/j15604136-202601-14

^1,2,3 Penza State University (Penza, Russia)

Keywords: Radiography interpretation agent-based approach artificial intelligence

Abstract

The extraction of Event-Related Potentials using electroencephalogram analysis is a well-established method for obtaining objective information about cognitive functions. To increase the signal‑to‑noise ratio Event-Related Potentials are often filtered. As an alternative, one can consider signal decomposition with subsequent selection of the components needed for analysis. The paper considers the application of the Empirical Wavelet Transform to perform this procedure.

Purpose – evaluation of Empirical Wavelet Transform for Event-Related Potential analysis.

On simulated data, Empirical Wavelet Transform substantially reduced background EEG while retaining the shape, amplitude of the ERP.

The results show that through the usage of Empirical Wavelet Transform it is possible to separate the Event-Related Potential signal using low volume of data.

Received: 08.12.2025
Approved after review: 15.12.2025
Accepted: 22.12.2025

How to cite

Мясникова Н.В., Долгих Л.А., Мясникова М.Г. Анализ вызванных потенциалов с использованием эмпирического вейвлет-преобразования // Биомедицинская радиоэлектроника. 2026. T. 29. № 1. С. 73−78. DOI: https:// doi.org/10.18127/j156 04136-202601-14

References

Grigor'ev F.N., Kuznecov N.A. Vydelenie vyzvannyh potencialov s ispol'zovaniem stohasticheskoj teorii fil'tra-cii». Informacionnye processy. 2014. T. 14. № 4. S. 285–294 (In Russian).
Quian Quiroga R., Garcia H. Single-trial event-related potentials with wavelet denoising. Clinical Neurophysiology. 2003. V. 114. № 2. P. 376–390.
Gilles J. Empirical Wavelet Transform. IEEE Transactions on Signal Processing. 2013. V. 61(16). P. 3999–4010.
Kappenman E.S., Luck, S.J. The effects of electrode impedance on data quality and statistical significance in ERP recordings. Psychophysiology. 2010. V. 47. P. 888–904.
Tseng S.Y., Chen R.C., Chong F.C., Kuo T.S. Evaluation of parametric methods in EEG signal analysis. Medical Engineering and Physics. 1995. V. 17. № 1. P. 71–78.

[1] Grigor'ev F.N., Kuznecov N.A. Vydelenie vyzvannyh potencialov s ispol'zovaniem stohasticheskoj teorii fil'tra-cii». Informacionnye processy. 2014. T. 14. № 4. S. 285–294 (In Russian).

[2] Quian Quiroga R., Garcia H. Single-trial event-related potentials with wavelet denoising. Clinical Neurophysiology. 2003. V. 114. № 2. P. 376–390.

[3] Gilles J. Empirical Wavelet Transform. IEEE Transactions on Signal Processing. 2013. V. 61(16). P. 3999–4010.

[4] Kappenman E.S., Luck, S.J. The effects of electrode impedance on data quality and statistical significance in ERP recordings. Psychophysiology. 2010. V. 47. P. 888–904.

[5] Tseng S.Y., Chen R.C., Chong F.C., Kuo T.S. Evaluation of parametric methods in EEG signal analysis. Medical Engineering and Physics. 1995. V. 17. № 1. P. 71–78.

Abstract

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