NCT04921020

Assessment of Eyelid Topology and Kinetics Based on Deep Learning Method

Department of Ophthalmology

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

Summary

This study plans to assess eyelid topology (such as margin reflex distance, eyelid contour, and corneal exposure area) and blinking (such as frequency, velocity, and duration), using deep learning method to automatically extract eyelid topological features, and to predict subtypes of levator function, using deep learning method to extract blinking features, in order to provide new ideas and means to assess eyelid topology and kinetics.

Conditions

• Eyelid Diseases

Interventions

Type	Name	Description
OTHER	Photography	Facial photographs and blinking videos are taken

Timeline

• Start date: 2020-08-01
• Primary completion: 2025-08-01
• Completion: 2026-08-01
• First posted: 2021-06-10
• Last updated: 2021-06-10

Locations

1 site across 1 country: China