What question did this study set out to answer?

This research aims to explore how artificial intelligence can enhance the study of visual systems, particularly in diagnosing glaucoma and analyzing eye movements.

May 2, 2026

Using Artificial Intelligence Methods to Study the Visual System

Key Points

This research aims to explore how artificial intelligence can enhance the study of visual systems, particularly in diagnosing glaucoma and analyzing eye movements.
Utilized computerized perimetry for visual field imaging related to glaucoma diagnosis.
Collected eye movement data using Tobii Pro Glasses 3 during VR video viewing.
Developed mathematical modeling to assess pupil movement dependencies.
Found that AI methods improve accuracy in diagnosing glaucoma based on visual field data.
Identified distinct fixation patterns of eye movements while viewing VR content.
Demonstrated potential applications of findings in monitoring glaucoma progression and enhancing user experience in VR.

Abstract

This paper describes ways of using various artificial intelligence techniques to study the human eye. The first data set is collected using computerized perimetry to study human visual field imaging and diagnose glaucoma. A method for image analysis using software is proposed. The second dataset is obtained as part of a Russian-Swiss experiment to collect and analyze eye-movement data using a Tobii Pro Glasses 3 device while viewing VR video. Eye movements and fixation patterns are studied along a recorded virtual travel route through the canton of Vaud. Methods are being developed for studying the dependencies in pupil movement using mathematical modeling. These findings can be used in medicine to assess the progression and deterioration of glaucoma in patients, as well as to study how VR video users allocate attention to tourist attractions.

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Using Artificial Intelligence Methods to Study the Visual System

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Abstract

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