Deep Neural Network model for convergence of Visual Fatigue and Computer Vision Disability

  • Jotheeswaran J
  • et al.
N/ACitations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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

Cite

CITATION STYLE

APA

Jotheeswaran, J., & Jain, S. (2020). Deep Neural Network model for convergence of Visual Fatigue and Computer Vision Disability. International Journal of Engineering and Advanced Technology, 9(3), 2599–2604. https://doi.org/10.35940/ijeat.c6007.029320

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free