# A practical introduction to wavelet analysis in electroretinography

## TL;DR

This paper introduces wavelet analysis methods for studying electroretinography signals, showing how they reveal time-frequency patterns that traditional methods miss.

## Contribution

The paper provides an accessible, formula-free overview of wavelet transforms and their practical application in ERG analysis.

## Key findings

- Wavelet analysis revealed time–frequency signatures not visible in raw ERG traces.
- DWT and CWT showed energy localization in specific frequency ranges for different ERG stimuli.
- The methods effectively captured the 30 Hz cone system response in flicker ERG recordings.

## Abstract

To provide a conceptual understanding of the continuous and discrete wavelet transforms (CWT, DWT) for clinical electroretinography (ERG) analysis, and how these methods uncover time–frequency features that complement traditional time-domain analysis.

A technical overview without the use of mathematical formula describing the basics of CWT and DWT and implementation considerations. We also review an example of four standard ISCEV full-field ERG (ffERG) recordings from a healthy 32-year-old male.

Wavelet analysis uncovered time–frequency signatures absent in raw traces. In DA 0.01 cd s/m2 DWT scalogram, energy localized in the 2–5 Hz range, with CWT scalograms corroborating these findings. In DA 3.0 cd s/m2, a broader frequency response is seen across 10, 20 and 40 Hz center frequencies. A similar progression was found in the LA 3.0 cd s/m2, with additional low energy indices at 80 and 160 Hz. For the LA 30 Hz flicker, all frequency and time–frequency profiles effectively replicated the 30 Hz response of the cone system.

CWT and DWT provide complementary and objective insight into ERG responses. Open-source MATLAB toolkit and step-by-step tutorial provided herein lower technical barriers and enable use by the broader community.