AI Revolutionizes Dry Eye Diagnosis with Blink Analysis

Dry Eye Disease (DED) is a common condition that causes discomfort and vision issues. Traditional methods to diagnose it can be invasive and time-consuming. But now, thanks to advancements in artificial intelligence (AI), diagnosing DED is becoming easier and more accurate.

Researchers have developed a new, non-invasive technology that uses AI to analyze blink patterns. Here's a simple breakdown of how it works:

The innovative system record blink videos under carefully controlled lighting conditions, capturing footage at 30 frames per second. These videos are then processed by a deep learning model, which analyzes blink patterns, interpalpebral height (IPH) and involuntary blink (IB) frequency. The system generates detailed blink profiles, correlating IB with DED symptoms to aid in diagnosis.

the result showed that Incomplete blinking (IB) was significantly more frequent in DED patients. The frequency and proportion of IB were closely associated with DED symptoms and signs.

This new method is non-Invasie which cause no uncomfortable procedures. It provides fast results without lengthy tests. the AI can precisely detect dry eye symptom through identifying the specific blink pattern and help doctors diagnose DEE efficiently.

Reference: Zheng Q, Wang L, Wen H, Ren Y, Huang S, Bai F, Li N, Craig JP, Tong L, Chen W. Impact of Incomplete Blinking Analyzed Using a Deep Learning Model With the Keratograph 5M in Dry Eye Disease. Transl Vis Sci Technol. 2022 Mar 2;11(3):38.