Leveraging Deep Learning to Optimize Individualized Eye-tracking for Early Visual Screening of Special Needs Children and Typical Preschoolers

What this Trial Is About

Early visual screening is crucial for supporting visual development, especially in children with visual impairments or developmental disabilities who cannot complete traditional vision tests. Researchers are evaluating a deep learning-based, individualized eye-tracking system to assess visual function, including visual acuity and visual field, in typical preschool children and infants under age three. This study aims to create a reliable, noninvasive visual screening method that meets the diverse needs of young children, including those with special needs. The study involves 1,300 participants divided into four groups: 300 adults to create reference data, 300 typically developing preschool children aged 3 to 5 years, 400 typically developing children under 3 years old, and 300 children with special needs such as developmental disabilities or visual impairments. Data collection will last from 15 to 22 months depending on the group. The study does not involve treatment but focuses on observation using the eye-tracking system. Participants will undergo assessments and video recordings with the Deep Visual Tracking System to measure visual acuity and visual field. Researchers will compare the system's accuracy to standard clinical evaluations over two months. They will also assess the reliability and validity of the eye-tracking measurements. The study includes children, adults, and special needs groups, with continuous monitoring to ensure data quality and participant safety throughout the observation period.

Visual Function Screening System With Special Needs Children and Typical Preschoolers