Validation of a Smartphone-based Intelligent Diagnosis and Measurement for Strabismus

Sun Yat-sen University

Status: Enrolling

Conditions: Vertical Strabismus; Strabismus; Exotropia; Esotropia

Treatments: Diagnostic Test: A new technology based on 3D reconstruction and deep learning algorithm to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests.

Study type: Observational

Funder types: Other

Identifiers

NCT05615519

DRStrabismus2022

Details and patient eligibility

About

The current measurement methods of strabismus include the corneal light reflection method, prism alternate covering, etc., which especially rely on the subjective experience of doctors, and there is a large error between different measurers， leading to serious underestimation of strabismus prevalence and insufficient care for strabismus patients. Here, the investigators established and validated an artificial intelligence system to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests. Three-dimensional reconstruction methods are used to digitize the parameters of head and eye positions. This system has been integrated into a smartphone platform to be further validated through hospital-based and population-based clinical trials.

Enrollment: 300 estimated patients

Sex: All

Ages: 3+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

The quality of facial videos should be clinically acceptable.

Trial design

300 participants in 1 patient group

Eligible participants for smartphone-based strabismus measurement and diagnosis

Description:

Facial videos dataset Facial videos were collected using smartphone and following the programmatic cover tests.

Treatment:

Diagnostic Test: A new technology based on 3D reconstruction and deep learning algorithm to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests.