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Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment Cover

Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment

Measurement Science Review
Volume 25 (2025): Issue 1 (February 2025)
By: Mohamed Yacin Sikkandar,  S. Sabarunisha Begum,  Ahmad Alassaf,  Ibrahim AlMohimeed,  Khalid Alhussaini,  Adham Aleid and  Abdulrahman Khalid Alhaidar  
Open Access
|Feb 2025

Figures & Tables

Fig. 1.

BSO-VAE-GAN architecture for artifact reduction.
BSO-VAE-GAN architecture for artifact reduction.

Fig. 2.

Comparison of MSE with the EEG+brain signal artifact.
Comparison of MSE with the EEG+brain signal artifact.

Fig. 3.

Comparison of MSE with the EEG+eye signal artifact.
Comparison of MSE with the EEG+eye signal artifact.

Fig. 4.

Comparison of MSE with the EEG+muscle signal artifact.
Comparison of MSE with the EEG+muscle signal artifact.

Accuracy performance of the proposed BrOpt_VAGAN model_

Mixtures of artifact componentsAccuracy [%]Error [%]
Pseudo-cleanbrain98.512.41
eye96.211.53
muscle97.312.74
Noisy inputbrain98.611.84
eye95.911.90
muscle93.512.56
DOI: https://doi.org/10.2478/msr-2025-0002 | Journal eISSN: 1335-8871
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Language: English
Page range: 10 - 14
Submitted on: Jun 4, 2024
|
Accepted on: Jan 16, 2025
|
Published on: Feb 24, 2025
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
EEG,
ECG,
artefacts,
EMG,
random noise,
neural network,
optimization,
fractional calculus
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2025 Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmad Alassaf, Ibrahim AlMohimeed, Khalid Alhussaini, Adham Aleid, Abdulrahman Khalid Alhaidar, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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