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Evaluation of Stereopsis Performance, Gaze Direction and Pupil Diameter in Post-COVID Syndrome Using Machine

Thomas S Knauer1, Christian Y Mardin1, Jürgen Rech2

  • 1Department of Ophthalmology, Universitätsklinikum, Friedrich-Alexander-University of Erlangen-Nürnberg, 91054 Erlangen, Germany.

Biomedicines
|November 27, 2025
PubMed
Summary

Virtual-reality oculomotor test systems (VR-OTS) can help diagnose Post-COVID Syndrome (PCS) by analyzing pupil diameter, gaze direction, and stereopsis. Pupil diameter features, particularly the index of pupillary activity, showed the most promise in distinguishing PCS patients from healthy individuals.

Keywords:
Post-COVIDVR-OTSlong COVID

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Area of Science:

  • Ophthalmology
  • Neurology
  • Medical Technology

Background:

  • Post-COVID Syndrome (PCS) presents persistent symptoms like fatigue and cognitive impairment, lacking objective diagnostic biomarkers.
  • Diagnosing PCS is challenging due to the absence of specific biomarkers, necessitating innovative assessment tools.
  • Virtual-reality oculomotor test systems (VR-OTS) offer a potential method for objectively measuring cognitive impairments associated with PCS.

Purpose of the Study:

  • To evaluate the effectiveness of VR-OTS in distinguishing patients with Post-COVID Syndrome (PCS) from healthy controls.
  • To determine which feature groups—stereopsis performance, gaze direction, or pupil diameter—are most effective in identifying PCS.
  • To identify specific VR-OTS features that provide the best diagnostic discrimination for PCS.

Main Methods:

  • Recruited 429 patients with PCS and healthy controls for VR-OTS measurements.
  • Extracted 95 features from VR-OTS data, categorized into gaze direction, pupil diameter, and stereopsis performance.
  • Utilized support vector machines (SVMs) with AUROC evaluation to assess feature group and individual feature predictive power.

Main Results:

  • Pupil diameter features achieved the highest discrimination (AUROC 0.73), followed by gaze direction (AUROC 0.68) and stereopsis performance (AUROC 0.66).
  • The index of pupillary activity (IPA) emerged as the single most predictive feature for distinguishing PCS patients.
  • More challenging VR-OTS tasks demonstrated higher predictive value across all feature categories.

Conclusions:

  • VR-OTS is a viable tool for differentiating between individuals with PCS and healthy controls.
  • Pupil diameter analysis, especially IPA, offers the most promising results for objective PCS assessment.
  • Future research should focus on optimizing feature selection from VR-OTS data for enhanced diagnostic accuracy in PCS.