Orientation and mobility test in virtual reality, a tool for quantitative assessment of functional vision: dataset and evaluation in healthy subjects

TL;DR

This study addresses the need for objective, scalable functional-vision assessment by introducing VR-S-O&M, a seated virtual reality orientation and mobility test. Built in Unity for HTC Vive Pro Eye, the protocol uses a torso-steering navigation metaphor and a destruction-based obstacle-detection mechanism across eight courses and six lighting levels, collecting rich motion and eye-tracking data from 42 healthy adults. The authors provide a first O&M behavior dataset in VR, derive per-run metrics such as Time duration, Time before first step, and Missed objects, and analyze how lighting, course configuration, and gaze behavior influence performance. Findings reveal a lighting threshold effect and a learning curve, with course-specific differences in obstacle detection that are linked to object features and gaze patterns, suggesting a richer, behavior-based approach to functional-vision scoring and longitudinal monitoring in clinical settings.

Abstract

The purpose of this study was to develop and evaluate a novel virtual reality seated orientation and mobility (VR-S-O&M) test protocol designed to assess functional vision. This study aims to provide a dataset of healthy subjects using this protocol and preliminary analyses. We introduced a VR-based O&M test protocol featuring a novel seated displacement method, diverse lighting conditions, and varying course configurations within a virtual environment. Normally sighted participants (N=42) completed the test, which required them to navigate a path and destroy identified obstacles. We assessed basic performance metrics, including time duration, number of missed objects, and time before the first step, under different environmental conditions to verify ecological validity. Additionally, we analyzed participants' behaviors regarding missed objects, demonstrating the potential of integrating behavioral and interactive data for a more precise functional vision assessment. Our VR-S-O&M test protocol, along with the first O&M behavior dataset, presents significant opportunities for developing more refined performance metrics for assessing functional vision and enhancing the quality of life.

Figures (19)

• Figure 1: A subject doing the VR-S-O&M test with his written consent.
• Figure 2: All courses used in this study.
• Figure 3: Examples of objects in different vertical positions. Green: low; Blue: medium; Yellow: high.
• Figure 4: Examples of objects in different horizontal positions.
• Figure 5: Feedback screen of what a subject sees during the virtual mobility test (The display in the VR HMD is different).