Student Research Symposium Program Portal: Submission #204

Abstract People around the world rely on computers every day to complete a wide variety of tasks, but frequent computer use can negatively impact the human body. One common issue is eye strain, as prolonged screen time can cause the eyes to become dry and fatigued. Blinking is essential for maintaining ocular homeostasis because it keeps the eye’s surface properly lubricated. Research by Ousler et al. (2014) shows that individuals with dry eyes spend more time with their eyes closed each minute than those without dry eyes in order to maintain this balance.
This study focuses on blinking behavior and examines whether blink frequency during computer use varies depending on the time of day. Understanding these patterns is important for supporting eye health, especially as digital device use continues to rise. However, accurately measuring blink rates is difficult without technological assistance.
To address this challenge, I developed a Python application to detect and track blink frequency. In this pilot study, the app will record blink rates during three time periods—morning, afternoon, and night. The long‑term goal is to create a tool that alerts users when their blink rate falls outside normal ranges, helping them make informed decisions and reduce the risk of eye strain.