Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID
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 impai...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-40263-w |
| _version_ | 1797559746867232768 |
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| author | Wolfgang Mehringer Maike Stoeve Daniel Krauss Matthias Ring Fritz Steussloff Moritz Güttes Julia Zott Bettina Hohberger Georg Michelson Bjoern Eskofier |
| author_facet | Wolfgang Mehringer Maike Stoeve Daniel Krauss Matthias Ring Fritz Steussloff Moritz Güttes Julia Zott Bettina Hohberger Georg Michelson Bjoern Eskofier |
| author_sort | Wolfgang Mehringer |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T17:49:41Z |
| format | Article |
| id | doaj.art-392c10b2b5ce4412ba25e7da9b043686 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:49:41Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-392c10b2b5ce4412ba25e7da9b0436862023-11-20T09:22:50ZengNature PortfolioScientific Reports2045-23222023-08-0113111610.1038/s41598-023-40263-wVirtual reality for assessing stereopsis performance and eye characteristics in Post-COVIDWolfgang Mehringer0Maike Stoeve1Daniel Krauss2Matthias Ring3Fritz Steussloff4Moritz Güttes5Julia Zott6Bettina Hohberger7Georg Michelson8Bjoern Eskofier9Machine Learning and Data Analytics Lab (MaD Lab), Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Machine Learning and Data Analytics Lab (MaD Lab), Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Machine Learning and Data Analytics Lab (MaD Lab), Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Machine Learning and Data Analytics Lab (MaD Lab), Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Department of Ophthalmology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergDepartment of Ophthalmology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergDepartment of Ophthalmology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergDepartment of Ophthalmology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergDepartment of Ophthalmology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergMachine Learning and Data Analytics Lab (MaD Lab), Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)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.https://doi.org/10.1038/s41598-023-40263-w |
| spellingShingle | Wolfgang Mehringer Maike Stoeve Daniel Krauss Matthias Ring Fritz Steussloff Moritz Güttes Julia Zott Bettina Hohberger Georg Michelson Bjoern Eskofier Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID Scientific Reports |
| title | Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID |
| title_full | Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID |
| title_fullStr | Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID |
| title_full_unstemmed | Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID |
| title_short | Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID |
| title_sort | virtual reality for assessing stereopsis performance and eye characteristics in post covid |
| url | https://doi.org/10.1038/s41598-023-40263-w |
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