Measuring Relative Afferent Pupillary Defect

Stopped early · Not applicable

Conditions studied: Relative Afferent Pupil Defect (RAPD)

In brief

The goal of this prospective reliability study is to test the effectiveness of a commercially available, off-the-shelf virtual reality head-mounted display (VR HMD) and machine learning (ML) algorithms in detecting Relative Afferent Pupillary Defect (RAPD) in a group of subjects with known RAPD and another group with no known RAPD. The main questions it aims to answer are: * Does the use of the VR HMD and ML to replace the standard of care swinging flashlight test provide a more reliable and objective pupil measurement to detect RAPD? * Can RAPD be detected by the VR HMD and ML algorithms at an earlier stage than the standard of care swinging light test? Participants will be asked to undergo the standard of care swinging flashlight test, have their pupils manually measured, then have the test repeated using the VR HMD and ML. Researchers will compare the measurements taken manually, following the standard of care swinging light test and those recorded by the VR HMD and ML to help answer the above questions.

Key facts

Study ID
NCT05799066
Run by
The University of Texas Medical Branch, Galveston
People needed
71
Starts
2023-05-04
Expected to finish
2026-03-06
Last updated by the study team
2026-06-03

Who can join

Age: 18 and older, up to 85. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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