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Related Experiment Video

Updated: Jan 1, 2026

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
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Predicting artificial visual field losses: A gaze-based inference study.

Erwan Joël David1, Pierre Lebranchu2, Matthieu Perreira Da Silva1

  • 1University of Nantes, Nantes, France.

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|December 24, 2019
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Summary
This summary is machine-generated.

Gaze tracking can identify artificial scotomas (vision loss areas) by analyzing saccade direction, amplitude, and velocity. This method aids in vision loss screening and monitoring.

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Area of Science:

  • Ophthalmology and Computer Science
  • Vision Science and Human-Computer Interaction

Background:

  • Visual field defects are a growing global health concern, with conditions like macular degeneration and glaucoma causing permanent vision loss.
  • Accurate identification and characterization of visual field loss are essential for developing effective screening, rehabilitation, and monitoring strategies.

Purpose of the Study:

  • To investigate the potential of using gaze features to differentiate between artificial scotoma (vision loss) conditions.
  • To identify key gaze characteristics that can predict the presence and type of visual field defects.

Main Methods:

  • Utilized a gaze-contingent paradigm with 54 participants viewing visual scenes under artificial central and peripheral scotomas of varying sizes.
  • Employed linear mixed models for comparing scotoma conditions and correlation/factorial analyses to identify data redundancies.
  • Applied hidden Markov models and recurrent neural networks to classify scotoma types based on gaze features.

Main Results:

  • Distinct saccade direction biases were observed depending on the type of artificial scotoma.
  • Saccade relative angle, amplitude, and peak velocity were identified as the most effective gaze features for differentiating between artificial scotoma conditions.
  • The study demonstrated the predictive power of gaze features in identifying scotoma characteristics.

Conclusions:

  • Gaze analysis, particularly focusing on saccade metrics, offers a promising non-invasive method for detecting and characterizing visual field defects.
  • The developed protocol and analytical tools can serve as valuable aids for identifying and discriminating between different types and sizes of artificial scotomas.
  • This approach has potential applications in clinical screening, rehabilitation, and ongoing patient monitoring for vision loss.