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Wavelet-Based Pattern ERG Biomarkers Outperform Temporal Amplitude Measures for Functional Stratification in Optic
Yousif J Shwetar1,2, Brett G Jeffrey3,4, Melissa A Haendel5,6
1Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Chapel Hill, NC, USA.
Translational Vision Science & Technology
|March 11, 2026
Summary
New Symlet-2 (sym2) discrete wavelet transform (DWT) features offer improved assessment of macular cone and retinal ganglion cell (RGC) function in optic nerve disease (OND). These novel PERG biomarkers demonstrate superior sensitivity for clinical trial endpoints.
Area of Science:
- Ophthalmology
- Biomedical Engineering
- Signal Processing
Background:
- Pattern electroretinography (PERG) is crucial for assessing retinal function.
- Traditional PERG analysis relies on canonical peaks, which may lack specificity for certain retinal cell types.
- Optic nerve disease (OND) affects retinal ganglion cells (RGCs), necessitating advanced diagnostic tools.
Purpose of the Study:
- To extend wavelet analysis of PERG from macular cone to RGC dysfunction in OND.
- To validate Symlet-2 (sym2) discrete wavelet transform (DWT) features for compartment-specific retinal assessment.
- To compare the efficacy of sym2 DWT features against traditional PERG amplitudes.
Main Methods:
- Analysis of PERG recordings from OND subjects and healthy volunteers (HVs) using the PERG-Institute of Applied Ophthalmobiology (IOBA) dataset.
- Quantification of five pre-selected sym2 DWT coefficients and a DWT energy index (7N).
- Correlation analysis with canonical amplitudes (|P50-N35|, |N95-P50|) and assessment of group separation (|rrb|).
Main Results:
- The sym2-D6-2 coefficient showed high correlation with |P50-N35| for both HV and OND groups.
- The sym2-A6-4 coefficient effectively differentiated between HV and OND groups (|rrb| = 0.549), outperforming |N95-P50| (|rrb| = 0.358).
- Bootstrap analysis confirmed sym2-A6-4's superiority over |P50-N35| and |N95-P50| in distinguishing OND from HVs.
Conclusions:
- Sym2 DWT features provide compartment-specific biomarkers for macular cone (sym2-D6-2) and RGC (sym2-A6-4) assessment.
- These novel biomarkers outperform traditional PERG peaks in sensitivity and specificity for OND.
- Further validation in diverse cohorts is recommended to confirm generalizability and clinical utility.
