Background: Premature newborns have a higher risk of abnormal visual development and visual impairment.
Objective: To develop a computational methodology to help assess functional vision in premature infants by tracking iris distances.
Methods: This experimental study was carried out with children up to two years old. A pattern of image capture with the visual stimulus was proposed to evaluate visual functions of vertical and horizontal visual tracking, visual field, vestibulo-ocular reflex, and fixation. The participants' visual responses were filmed to compose a dataset and develop a detection algorithm using the OpenCV library allied with FaceMesh for the detection and selection of the face, detection of specific facial points and tracking of the iris positions is done. A feasibility study was also conducted from the videos processed by the software.
Results: Forty-one children of different ages and diagnoses participated in the experimental study, forming a robust dataset. The software resulted in the tracking of iris positions during visual function evaluation stimuli. Furthermore, in the feasibility study, 8 children participated, divided into Pre-term and Term groups. There was no statistical difference in any visual variable analyzed in the comparison between groups.
Conclusion: The computational methodology developed was able to track the distances traveled by the iris, and thus can be used to help assess visual function in children.
Keywords: Eye-tracking technology; dataset; eye movements; preterm birth; software; vision screening.