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Abstract

Research in Medical & Engineering Sciences

Robustness of EFD in Noisy Conditions: A Comparative Study with EWT for EEG and Synthesized Signal

  • Open or CloseSaba Haji Molla Rabie1, Sedigheh Ghofrani2,3*, Mahdi Eslami4 and Hamideh Barghamadi1

    1Department of Medical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

    2Department of Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

    3Research Center of Modeling and Optimization in science and Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

    4Department of Electrical and Computer Engineering, Science and Research Branch Islamic Azad University, Tehran, Iran

    *Corresponding author:Sedigheh Ghofrani, Department of Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran and Department of Electrical and Computer Engineering, Science and Research Branch Islamic Azad University, Tehran, Iran

Submission: January 08, 2025;Published: April 25, 2025

DOI: 10.31031/RMES.2025.11.000772

ISSN: 2576-8816
Volume11 Issue 5

Abstract

Objective: This paper compares two empirical signal decomposition methods, the Empirical Wavelet Transform (EWT) and the Empirical Fourier Decomposition (EFD), focusing on their performance in decomposing synthetic signals and real EEG data, particularly in noisy environments. The used metrics are Signal-to-Noise Ratio (SNR), Percentage Root Mean Square Error (PRMSE), and Correlation (Corr). For the different scenarios, EFD-based approach shows competitive performance compared to EWT and other methods as well.

Keywords:Empirical Wavelet transform; Empirical fourier decomposition; Noise robustness; SNR; PRMSE; Corr

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