
Deep Neural Network model for convergence of Visual Fatigue and Computer Vision Disability
Author(s) -
Jeevanandam Jotheeswaran,
Surbhi Jain
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c6007.029320
Subject(s) - computer science , field (mathematics) , visual field , artificial neural network , artificial intelligence , human–computer interaction , computer vision , psychology , mathematics , neuroscience , pure mathematics
The expanded utilization of blue screens in the work environment and home has realized the advancement of various health concerns. Numerous people who uses blue screens such as Computers, Tablets, Mobiles and Etc., report an elevated level of occupation related grievances and side effects, including visual fatigue and stress. The complex of eye and vision issues identified with close to such usages are called as "computer vision syndrome". In this research work, we study and understand the flow level of a user, while using a smart phone. The study of the flow level will majorly depend on the eye-activity of the user. The data mentioned below is carefully recorded after examining the activity of eyes including the size of the pupil, blink rate, and blink duration. The purpose of this study is to understand the connection between the flow level and the activity of the eyes. A clear understanding of this connection could prove to be very useful information in the computer vision field. Additionally, this can also help a lot to understand about Visual Fatigue caused by Digital Medium