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Computational Analysis of Eye-Strain for Digital Screens based on Eye Tracking Studies

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Computational Analysis of Eye-Strain for Digital Screens based on Eye Tracking Studies

Parisay, Mohsen (2021) Computational Analysis of Eye-Strain for Digital Screens based on Eye Tracking Studies. PhD thesis, Concordia University.

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Abstract

Computer vision syndrome (CVS) is composed of multiple eye vision problems due to the prolonged use of digital displays, including tablets and smartphones. These problems were shown to affect visual comfort as well as work productivity in both adults and teenagers. CVS causes eye and vision symptoms such as eye-strain, eye burn, dry eyes, double vision, and blurred vision. CVS, which causes severe vision and muscular problems due to repeated eye movements and excessive eye focus on computer screens, is a cause of work-related stress. In this thesis, we address this problem and present three general-purpose mathematical compound models for assessing eye-strain in eye-tracking applications, namely (1) Fixation-based Eye fatigue Load Index (FELiX), (2) Index of Difficulty for Eye-tracking Applications (IDEA), and (3) Eye-Strain Probation Model (ESPiM) based on eye-tracking parameters and subjective ratings to measure, predict, and compare the amount of fatigue or cognitive workload during target selection tasks for different user groups or interaction techniques. The ESPiM model is the outcome of both FELiX and IDEA, which benefit from direct subjective rating and, therefore, can be applied to assess the ESPiM model's efficacy. We present experiments and user studies that show that these models can measure potential eye-strain levels on individuals based on physical circumstances such as screen resolution and target positions per time.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (PhD)
Authors:Parisay, Mohsen
Institution:Concordia University
Degree Name:Ph. D.
Program:Computer Science
Date:22 October 2021
Thesis Supervisor(s):Kersten-Oertel, Marta and Poullis, Charalambos
ID Code:990249
Deposited By: mohsen parisay
Deposited On:16 Jun 2022 14:42
Last Modified:16 Jun 2022 14:42
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