Development and Validation of an Automated Self-administered Visual Acuity System

NCT06540001 | Not Yet Recruiting

• 1 other identifier: 2024/00157
• Study Type: interventional
• Target: 100
• Locations: 0 countries
• Sites: N/A

Brief Summary

Visual acuity tests, commonly conducted in clinics and used for health screenings, are becoming more in demand due to an aging population. Current online self-eye check apps are limited as they don\'t accurately reflect true distance vision assessed in clinical settings. These tests, performed by trained personnel, are time-consuming and can cause delays in clinics. This project aims to develop an automated Visual Acuity (VA) station using AI technologies like speech-to-text and computer vision, hypothesizing that it can match the accuracy of manual assessments by clinic staff, thus potentially reducing waiting times and improving efficiency.

Conditions

Visual Impairment

Keywords

Visual acuity

Outcome Measures

Primary Outcomes (1)

• Best corrected visual acuity with and without pinhole using Snellen letters and numbers

  Best corrected visual acuity will be expressed in metres (e.g. 6/6-1), and will be converted to LogMAR for analysis.

  1 year

Study Arms (1)

Patients will undergo both automated and manual visual acuity testing

EXPERIMENTAL

Patient will perform manual visual acuity first, then be guided to another room to have the visual acuity tested on the automated VA device

Device: Automated visual acuity

Interventions

Automated visual acuity DEVICE

The automated visual acuity device is developed in collaboration with Tan Tock Seng Hospital, Singapore Institute of Technology and Nanyang Technological University. It uses artificial intelligence for pose estimation and speech recognition to infer if the participant is reading the correct letters displayed on the screen.

Patients will undergo both automated and manual visual acuity testing

Eligibility Criteria

• Age: 21 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients age \>21 and able to give consent
• Patients who have at least counting finger vision
• Patients who is able to speak in an audible and clear voice
• Patients who is able to use a digital device independently (e.g. handphone)

You may not qualify if:

• Patients on wheelchair/ walking aids
• Patients with hearing difficulties
• Patients with speech difficulties
• Patients who have cognitive impairment
• Patients who are hemiplegic/ motor dysfunction
• Patients who have vision worse than counting fingers
• Patients who are pregnant

Sponsors & Collaborators

• Tan Tock Seng Hospital: lead
• Singapore Institute of Technology: collaborator
• Nanyang Technological University: collaborator
• Lee Kong Chian School of Medicine, Nanyang Technological University: collaborator

MeSH Terms

Conditions

Vision Disorders

Condition Hierarchy (Ancestors)

Sensation Disorders; Neurologic Manifestations; Nervous System Diseases; Eye Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Kelvin Z Li., MBBS, MTech, FRCOphth

CONTACT

+6562566011; contact@ttsh.com.sg

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Consultant

Study Record Dates

• First Submitted: July 27, 2024
• First Posted: August 6, 2024
• Study Start: August 1, 2024
• Primary Completion: October 31, 2024
• Study Completion: August 1, 2025
• Last Updated: August 6, 2024

Record last verified: 2024-08

Data Sharing

• IPD Sharing: Will not share