Kinetic Perimetry on Virtual Reality Headset
IEEE Transactions on Biomedical Circuits and Systems, ISSN: 1940-9990, Vol: 17, Issue: 3, Page: 413-419
2023
- 4Citations
- 22Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations4
- Citation Indexes4
- CrossRef2
- Captures22
- Readers22
- 22
Article Description
Objective: We present a portable automatic kinetic perimeter based on a virtual reality (VR) headset device as an innovative and alternative solution for the screening of clinical visual fields. We compared the performances of our solution with a gold standard perimeter, validating the test on healthy subjects. Methods: The system is composed of an Oculus Quest 2 VR headset with a clicker for participant response feedback. An Android app was designed in Unity to generate moving stimuli along vectors, following a standard Goldmann kinetic perimetry approach. Sensitivity thresholds are obtained by moving centripetally three different targets (V/4e, IV/1e, III/1e) along 24 or 12 vectors from an area of non-seeing to an area of seeing and then transmitted wirelessly to a PC. A Python real-time algorithm processes the incoming kinetic results and displays the hill of vision in a two-dimensional map (isopter). We involved 21 subjects (5 males and 16 females, age range 22-73 years) for a total of 42 eyes tested with our proposed solution, and results were compared with a Humphrey visual field analyzer to test reproducibility and efficacy. Results: isopters generated with the Oculus headset were in good agreement with those acquired with a commercial device (Pearson's correlation values r > 0.83 for each target). Conclusions: we demonstrate the feasibility of VR kinetic perimetry by comparing performances between our system and a clinically used perimeter in healthy subjects. Significance: proposed device leads the way for a portable and more accessible visual field test, overcoming challenges in current kinetic perimetry practices.
Bibliographic Details
Institute of Electrical and Electronics Engineers (IEEE)
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know