Detection of eye strain due to usage of electronic devices
A machine learning based approach
Keywords:
eye strain, electronic devices, machine learningAbstract
The development of ICT has led to a mobile revolution. Mobile phones, internet, social networking, emails, video conferencing and much more has changed the way we work, learn and communicate (Bian M, 2015). Technology brings with itself certain challenges with respect to the harmful impact of prolonged usage of digital devices on the users’ health. People who excessively use electronic devices develop musculoskeletal syndromes. Eyes, shoulder and neck muscles, arm, and wrist are most affected with prolonged usage of digital devices. The aim of this research is to study and list the problems associated with eyes due to the prolonged usage of electronic gadgets with screen. For this purpose, 350 people (170 females, 180 males) from different ages and jobs were asked about eye health with the help of a questionnaire. The factors to detect eye strain and fatigue were collected from literature as well as through a set of interviews. The factors act as the variables for the factor analysis and random forest method has been used for classification. The results of this study implicates the factors that can be used to detect eye strain and fatigue in the users of digital devices.
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