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Related Experiment Video

Updated: Jan 9, 2026

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Improving the reliability of the pattern electroretinogram with adaptive filtering.

Zachary George Angus1, Alexander Sarossy2, Puneet Parihar3

  • 1Faculty of Medicine, Nursing and Health Sciences, Monash University, 27 Rainforest Walk, Clayton, Melbourne, 3168, VIC, Australia. zacangus87@gmail.com.

Scientific Reports
|December 6, 2025
PubMed
Summary
This summary is machine-generated.

Adaptive denoising techniques significantly enhance the reliability of pattern electroretinogram (PERG) tests. Empirical Wavelet Transform showed the most improvement, aiding in diagnosing retinal and optic nerve diseases.

Keywords:
DenoisingEMDEWTElectroretinographyEmpirical mode decompositionPattern electroretinogramVMD

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Area of Science:

  • Ophthalmology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electrophysiological tests are crucial for diagnosing eye diseases.
  • Pattern electroretinogram (PERG) is valuable for central retinal and optic nerve conditions.
  • PERG signals are often small and noisy, limiting their clinical utility.

Purpose of the Study:

  • To improve the reliability and utility of PERG using adaptive denoising techniques.
  • To evaluate the effectiveness of different adaptive filtering algorithms on PERG signals.

Main Methods:

  • PERG recordings were obtained from 70 eyes of 36 patients following ISCEV protocols.
  • Two recordings were taken per eye to assess test-retest reliability.
  • Five adaptive filtering algorithms were applied for denoising, including Empirical Wavelet Transform.

Main Results:

  • Adaptive denoising generally improved test-retest reliability (ICC and CoR).
  • Empirical Wavelet Transform demonstrated the best performance, significantly enhancing ICC and reducing CoR.
  • Improvements in reliability suggest increased diagnostic accuracy for PERG.

Conclusions:

  • Adaptive denoising algorithms, particularly Empirical Wavelet Transform, can significantly improve PERG reliability.
  • These techniques offer a promising approach to overcome signal limitations in PERG testing.
  • Enhanced PERG reliability can aid in the assessment, diagnosis, and management of visual system diseases.