Group comparisons of the individual electroretinogram time trajectories for the ascending limb of the b-wave using a raw and registered time series

Marek Brabec, Paul Constable, Dorothy Thompson, Fernando Marmolejo-Ramos

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
42 Downloads (Pure)

Abstract

Objectives
The electroretinogram is a clinical test commonly used in the diagnosis of retinal disorders with the peak time and amplitude of the a- and b-waves used as the main indicators of retinal function. However, subtle changes that affect the shape of the electroretinogram waveform may occur in the early stages of disease or in conditions that have a neurodevelopmental or neurodegenerative origin. In such cases, we introduce a statistical approach to mathematically model the shape of the electroretinogram waveform that may aid clinicians and researchers using the electroretinogram or other biological signal recordings to identify morphological features in the waveforms that may not be captured by the time or time–frequency domains of the waveforms. We present a statistical graphics-based analysis of the ascending limb of the b-wave (AL-b) of the electroretinogram in children with and without a diagnosis of autism spectrum disorder (ASD) with a narrative explanation of the statistical approach to illustrate how different features of the waveform based on location and scale derived from raw and registered time series can reveal subtle differences between the groups.

Results
Analysis of the raw time trajectories confirmed findings of previous studies with a reduced and delayed b-wave amplitude in ASD. However, when the individual time trajectories were registered then group differences were visible in the mean amplitude at registered time ~ 0.6 suggesting a novel method to differentiate groups using registration of the ERG waveform.
Original languageEnglish
Article number238
Number of pages9
JournalBMC Research Notes
Volume16
Issue number1
DOIs
Publication statusPublished - 29 Sept 2023

Keywords

  • Electroretinogram
  • Time domain analysis
  • Curve registration
  • b-Wave

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