VisualR: A novel and scalable solution for assessing visual function using virtual reality

Diagnosis and treatment of progressive eye diseases require effective monitoring of visual structure and function. However, current methods for measuring visual function are limited in accuracy, reliability, and usability. We propose a novel approach that leverages virtual reality (VR) technology to overcome these challenges, enabling more comprehensive measurements of visual function endpoints.

We developed VisualR, a low-cost VR-based application that consists of a smartphone app and a simple VR headset. The virtual environment allows precise control of visual stimuli, including the field of view, separation of visual input to the left and right eyes, control of visual angles and blocking of background visual noise. We developed novel tests for metamorphopsia, contrast sensitivity and reading speed that can be performed by following simple instructions and providing verbal responses to visual cues, without expert supervision. The smartphone app operates offline and processes all data locally.

We conducted empirical evaluations, including measurements of screen luminance, and performed simulations of psychometric functions to test the feasibility of building a visual function test device using widely available, inexpensive consumer-grade hardware. Our findings demonstrate the technical viability of this approach, and its potential to measure visual function endpoints during clinical development of new treatments or to support disease diagnosis and monitoring. We open-sourced the VisualR application code and provide guidelines for creating reliable and user-friendly VR-based tests.

Our results suggest that VR technology can open a new paradigm in visual function testing, and invite the wider community to build upon our work.

Visual function describes how well the eyes can see and process basic visual information. Testing visual function is important for diagnosing and treating eye diseases that can affect vision, but current methods for measuring it are often unreliable or too complex to be performed by users without professional assistance. We propose a novel approach that uses VR technology to enable affordable and user-friendly assessments of visual function. We developed VisualR, a VR-based application that runs on a smartphone together with a simple VR headset. VisualR enables users to perform various vision function tests by following simple instructions and providing verbal responses to the visual stimuli displayed on the screen. As VisualR is smartphone-based, it eliminates the need for costly or specialized equipment. Our work demonstrates the technical feasibility and potential of creating affordable, accessible VR-based visual test devices. We open-sourced the code of VisualR and invite the broader community to build upon this work.