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A Machine Learning based Eye Tracking Framework to detect Zoom Fatigue

Patel, Anjuli (2021) A Machine Learning based Eye Tracking Framework to detect Zoom Fatigue. Masters thesis, Dublin, National College of Ireland.

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Zoom Fatigue is a form of mental fatigue that occurs in online users with increased use of video conferencing. Mental fatigue can be detected using eye movements. However, detecting eye movements in online users is a challenge. This research proposes a Machine Learning based Eye Tracking Framework (MLETF) to detect zoom fatigue in individuals by analysing the data collected by eye tracking device and other influencing variables (such as sleepiness, personality, etc.). An experiment was conducted with 31 participants, where they wore an eye tracker device while watching a lecture on Mobile Application Development. The online users were given by two questionnaires, one with the summary and test from the content of the video and the second a personality questionnaire. The classification performance analysis of the supervised learning algorithms showed Ada-Boost was the most suitable algorithm to detect Zoom fatigue in individuals with accuracy of 86%. The result of this research demonstrates the feasibility of applying wearable eye-tracking technology to identify zoom fatigue with online users of video conferencing.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Eye Tracker; Zoom Fatigue; Machine Learning; SVM; KNN; Ada-Boost; Logistic Regression; Decision Tree
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine > Personal Health and Hygiene
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Clara Chan
Date Deposited: 11 Dec 2021 12:17
Last Modified: 11 Dec 2021 12:17

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