ArticleScientific reports2023
Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Task-Evoked Pupillary Dynamics Are Altered in Post-COVID Syndrome.Medical sciences (Basel, Switzerland) · 2026Article
- 3D Virtual Reality Performance Metrics as a Future Fatigue Biomarker in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).Biomedicines · 2026Article
- Evaluation of Stereopsis Performance, Gaze Direction and Pupil Diameter in Post-COVID Syndrome Using Machine Learning.Biomedicines · 2025Article
- Physical exertion does not lead to a change in the time taken to correctly recognize stereoscopic stimuli in changing horizontal disparity levels.Frontiers in physiology · 2025Article
- A case-control study of reaction time deficits in a 3D virtual reality in patients with Post-COVID syndrome.Scientific reports · 2024Article
- Review
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 2019, we faced a pandemic due to the coronavirus disease (COVID-19), with millions of confirmed cases and reported deaths. Even in recovered patients, symptoms can be persistent over weeks, termed Post-COVID. In addition to common symptoms of fatigue, muscle weakness, and cognitive impairments, visual impairments have been reported. Automatic classification of COVID and Post-COVID is researched based on blood samples and radiation-based procedures, among others. However, a symptom-oriented assessment for visual impairments is still missing. Thus, we propose a Virtual Reality environment in which stereoscopic stimuli are displayed to test the patient's stereopsis performance. While performing the visual tasks, the eyes' gaze and pupil diameter are recorded. We collected data from 15 controls and 20 Post-COVID patients in a study. Therefrom, we extracted features of three main data groups, stereopsis performance, pupil diameter, and gaze behavior, and trained various classifiers. The Random Forest classifier achieved the best result with 71% accuracy. The recorded data support the classification result showing worse stereopsis performance and eye movement alterations in Post-COVID. There are limitations in the study design, comprising a small sample size and the use of an eye tracking system.
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Registered trials
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