Student Research Symposium Program Portal: Submission #204

Abstract Many people around the world use computers every day for multiple purposes. In turn, the use of computers can affect the body in several ways. For example, the eyes can become dry much easier while staring at a computer screen. Blinking is crucial for the eye to achieve homeostasis, which involves keeping the eye moist. Research by Ousler et al. (2014) indicates that people with dry eyes spend more time with their eyes closed in a minute than those that don’t have dry eyes to achieve homeostasis. This research is aimed specifically at the blinking of the eye, and sees if there are any correlations between blinking behavior (length and frequency) while using a computer and the time of the day which it is used in. Blinking is essential to eye health and would be crucial to understanding any patterns which may affect them. However, collecting blink rate data is impossible to track without technology. To solve this, I will be creating a Python app with machine learning that will measure and track blink rates. In this pilot study the trained app will record the blink rate in two different day time segments, namely day and nighttime (day would be time before noon, night would be between 6-10pm). The goal of this research is to develop an app that can notify a user when their blink rate is outside normal bounds so that the user can make educated choices and reduce the possibility of eye strain.