Using artificial intelligence methods for the studyed visual analyzer

TL;DR

This paper explores AI techniques applied to eye analysis, including glaucoma diagnosis and eye movement tracking during VR experiences, proposing new software analysis methods and mathematical models.

Contribution

It introduces novel AI-based methods for analyzing eye images and movements, integrating VR data for medical and attention studies.

Findings

AI methods effectively visualize visual fields and diagnose glaucoma.

Eye movement analysis reveals dependencies useful for medical assessments.

VR-based eye tracking offers insights into attention and eye health.

Abstract

The paper describes how various techniques for applying artificial intelligence to the study of human eyes are utilized. The first dataset was collected using computerized perimetry to investigate the visualization of the human visual field and the diagnosis of glaucoma. A method to analyze the image using software tools is proposed. The second dataset was obtained, as part of the implementation of a Russian-Swiss experiment to collect and analyze eye movement data using the Tobii Pro Glasses 3 device on VR video. Eye movements and focus on the recorded route of a virtual journey through the canton of Vaud were investigated. Methods are being developed to investigate the dependencies of eye pupil movements using mathematical modelling. VR-video users can use these studies in medicine to assess the course and deterioration of glaucoma patients and to study the mechanisms of attention to tourist attractions.