Virtual Reality Application for Vestibular/Ocular Motor Screening: Current Clinical Protocol Versus a Novel Prototype.

BACKGROUND: Virtual reality (VR) has been explored to improve baseline and postinjury assessments in sport-related concussion (SRC). Some experience symptoms related to VR, unrelated to concussion. This may deter use of vestibular/ocular motor screening (VOMS) using VR. Baseline VR VOMS symptomatology differentiates baseline from overall symptomatology. HYPOTHESIS: There will be no difference between current clinical manual VOMS (MAN), a clinical prototype (PRO), and VR for symptom provocation change score (SPCS) and near point of convergence (NPC) average score in a healthy population and sex differences among the 3 modes of administration. STUDY DESIGN: Cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: A total of 688 National Collegiate Athletic Association Division I student-athletes completed VOMS using 3 methods (MAN, N = 111; female athletes, N = 47; male athletes, N = 64; average age, 21 years; PRO, N = 365; female athletes, N = 154; male athletes, N = 211; average age, 21 years; VR, N = 212; female athletes, N = 78; male athletes, N = 134; average age = 20 years) over a 3-year period (2019-2021) during annual baseline testing. Exclusion criteria were as follows: self-reported motion sickness in the past 6 months, existing or previous neurological insult, attention deficit hyperactivity disorder, learning disabilities, or noncorrected vision impairment. Administration of MAN followed the current clinical protocols, PRO used a novel prototype, and VR used an HTC Vive Pro Eye head mounted display. Symptom provocation was compared using Mann-Whitney U tests across each VOMS subtest with total SPCS and NPC average by each method. RESULTS: MAN had significantly (P < 0.01) more baseline SPCS (MAN = 0.466 ± 1.165, PRO = 0.163 ± 0.644, VR = 0.161 ± 0.933) and significantly (P < 0.01) and more SPCS (MAN = 0.396 ± 1.081, PRO = 0.128 ± 0.427, VR = 0.48 ± 0.845) when compared with PRO and VR. NPC average measurements for VR (average, 2.99 ± 0.684 cm) were significantly greater than MAN (average, 2.91 ± 3.35 cm; P < 0.01; Cohen's d = 0.03) and PRO (average, 2.21 ± 1.81 cm; P < 0.01; Cohen's d = 0.57). For sex differences, female athletes reported greater SPCS with PRO (female athletes, 0.29 ± 0.87; male athletes, 0.06 ± 0.29; P < 0.01) but not in VR or MAN. CONCLUSION: Using a VR system to administer the VOMS may not elicit additional symptoms, resulting in fewer false positives and is somewhat stable between sexes. CLINICAL RELEVANCE: VOMS may allow for standardization among administrators and reduce possible false positives.

Eye Tracking in Virtual Reality: a Broad Review of Applications and Challenges.

Eye tracking is becoming increasingly available in head-mounted virtual reality displays with various headsets with integrated eye trackers already commercially available. The applications of eye tracking in virtual reality are highly diversified and span multiple disciplines. As a result, the number of peer-reviewed publications that study eye tracking applications has surged in recent years. We performed a broad review to comprehensively search academic literature databases with the aim of assessing the extent of published research dealing with applications of eye tracking in virtual reality, and highlighting challenges, limitations and areas for future research.

VR Sickness Adaptation With Ramped Optic Flow Transfers From Abstract To Realistic Environments.

VR sickness is a major concern for many users as VR continues its expansion towards widespread everyday use. VR sickness is thought to arise, at least in part, due to the user's intolerance of conflict between the visually simulated self-motion and actual physical movement. Many mitigation strategies involve consistently modifying the visual stimulus to reduce its impact on the user, but this individualized approach can have drawbacks in terms of complexity of implementation and non-uniformity of user experience. This study presents a novel alternative approach that involves training the user to better tolerate the adverse stimulus by tapping into natural adaptive perceptual mechanisms. In this study, we recruited users with limited VR experience that reported susceptibility to VR sickness. Baseline sickness was measured as participants navigated a rich and naturalistic visual environment. Then, on successive days, participants were exposed to optic flow in a more abstract visual environment, and strength of the optic flow was successively increased by increasing the visual contrast of the scene, because strength of optic flow and the resulting vection are thought to be major causes of VR sickness. Sickness measures decreased on successive days, indicating that adaptation was successful. On the final day, participants were again exposed to the rich and naturalistic visual environment, and the adaptation was maintained, demonstrating that it is possible for adaptation to transfer from more abstract to richer and more naturalistic environments. These results demonstrate that gradual adaptation to increasing optic flow strength in well-controlled, abstract environments allows users to gradually reduce their susceptibility to sickness, thereby increasing VR accessibility for those prone to sickness.

GazeMetrics: An Open-Source Tool for Measuring the Data Quality of HMD-based Eye Trackers.

As virtual reality (VR) garners more attention for eye tracking research, knowledge of accuracy and precision of head-mounted display (HMD) based eye trackers becomes increasingly necessary. It is tempting to rely on manufacturer-provided information about the accuracy and precision of an eye tracker. However, unless data is collected under ideal conditions, these values seldom align with on-site metrics. Therefore, best practices dictate that accuracy and precision should be measured and reported for each study. To address this issue, we provide a novel open-source suite for rigorously measuring accuracy and precision for use with a variety of HMD-based eye trackers. This tool is customizable without having to alter the source code, but changes to the code allow for further alteration. The outputs are available in real time and easy to interpret, making eye tracking with VR more approachable for all users.