ArticleBioengineering (Basel, Switzerland)2023
OculusGraphy: Signal Analysis of the Electroretinogram in a Rabbit Model of Endophthalmitis Using Discrete and Continuous Wavelet Transforms.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Wavelet-Based Pattern ERG Biomarkers Outperform Temporal Amplitude Measures for Functional Stratification in Optic Nerve Disease.Translational vision science & technology · 2026Article
- Multidimensional Quantification of Macular Cone Activity in Pattern Electroretinography Using Discrete Wavelet Transform.Translational vision science & technology · 2025Article
- Remodeling the light-adapted electroretinogram using a bayesian statistical approach.BMC research notes · 2025Article
- Spectral Analysis of Light-Adapted Electroretinograms in Neurodevelopmental Disorders: Classification with Machine Learning.Bioengineering (Basel, Switzerland) · 2024Article
- Generating Synthetic Light-Adapted Electroretinogram Waveforms Using Artificial Intelligence to Improve Classification of Retinal Conditions in Under-Represented Populations.Journal of ophthalmology · 2024Article
- Enhancing Electroretinogram Classification with Multi-Wavelet Analysis and Visual Transformer.Sensors (Basel, Switzerland) · 2023Article
- Optimal Combination of Mother Wavelet and AI Model for Precise Classification of Pediatric Electroretinogram Signals.Sensors (Basel, Switzerland) · 2023Article
- Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies.Frontiers in neuroscience · 2023Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
Abstract
backgroundThe electroretinogram is a clinical test used to assess the function of the photoreceptors and retinal circuits of various cells in the eye, with the recorded waveform being the result of the summated response of neural generators across the retina.
methodsThe present investigation involved an analysis of the electroretinogram waveform in both the time and time-frequency domains through the utilization of the discrete wavelet transform and continuous wavelet transform techniques. The primary aim of this study was to monitor and evaluate the effects of treatment in a New Zealand rabbit model of endophthalmitis via electroretinogram waveform analysis and to compare these with normal human electroretinograms.
resultsThe wavelet scalograms were analyzed using various mother wavelets, including the Daubechies, Ricker, Wavelet Biorthogonal 3.1 (bior3.1), Morlet, Haar, and Gaussian wavelets. Distinctive variances were identified in the wavelet scalograms between rabbit and human electroretinograms. The wavelet scalograms in the rabbit model of endophthalmitis showed recovery with treatment in parallel with the time-domain features.
conclusionsThe study compared adult, child, and rabbit electroretinogram responses using DWT and CWT, finding that adult signals had higher power than child signals, and that rabbit signals showed differences in the a-wave and b-wave depending on the type of response tested, while the Haar wavelet was found to be superior in visualizing frequency components in electrophysiological signals for following the treatment of endophthalmitis and may give additional outcome measures for the management of retinal disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.