Automated Non-Supervised Eye Disorder Screening System Using Virtual Reality.

Lijing Chen, Yinan Miao, Hyeonwoo Nam, Hwan Heo, Sang Woo Park, Gyuhae Park
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Abstract

Background: Neglecting eye disorders can lead to visual impairment or even vision loss, making early diagnosis and medical treatment crucial. This paper presents the development of an automated non-supervised eye disorder screening system that utilises Virtual Reality (VR) to provide a preliminary screening for common eye disorders.

Methods: The system integrates advanced pupil-tracking techniques, image-processing methods, and eye disorder screening algorithms into one package for comprehensive eye disorder monitoring, including a strabismus test, a pupil test, and a contrast sensitivity test. Patients can wear a VR headset and use a joystick to interact with the VR scenario.

Results: The system is validated through experiments conducted on both healthy subjects and patients in hospitals, demonstrating an agreement rate exceeding 90% when compared to diagnoses by doctors.

Conclusions: The test results highlight its potential for real-world applications, ultimately improving the accessibility of early screening for eye disorders and remote healthcare.

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