Ascertaining DES (Digital Eye Strain) Symptoms Using Machine Learning Libraries

Abstract

In the IT (Information Technology) funded society we are spending a lot of time in front of digital devices that includes TV, computer screen, mobile, digital projectors. Now a days these digital devices have become part of societal obligation. Keeping the current scenario in concern, we cannot avoid these devices as they keep us socially updated and globally connected but on the other hand they leave a bad impact on our vital organ: eye. Due to excessive screen time we all have signs of CVS (Computer Vision Syndrome). To mitigate these CVS related issues we have to be caution for its symptoms and take preventive actions. This research piece is a contribution in the CVS symptoms caution method. Researchers have tried to find out the ocular symptoms and try to trace them while user is interacting with its digital device. The symptoms that are considered in this research piece are blinking, Redness, Itching and squeezing. The flow of paper will define how these things can be traced from video clip or the frames derived from video clip.