Virtual reality for assessing stereopsis performance and eye characteristics in Post-COVID.

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.

MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data.

Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have been developed without addressing adaptability, usability, and user experience. Therefore, we developed a generic open-source Python package focusing on adaptability, usability, and user experience. The developed package, Machine Learning and Data Analytics (MaD) GUI, enables developers to rapidly create a GUI for their specific use case. Furthermore, MaD GUI enables domain experts without programming knowledge to annotate time-series data and apply algorithms to it. We conducted a small-scale study with participants from three international universities to test the adaptability of MaD GUI by developers and to test the user interface by clinicians as representatives of domain experts. MaD GUI saves up to 75% of time in contrast to using a state-of-the-art package. In line with this, subjective ratings regarding usability and user experience show that MaD GUI is preferred over a state-of-the-art package by developers and clinicians. MaD GUI reduces the effort of developers in creating GUIs for time-series analysis and offers similar usability and user experience for clinicians as a state-of-the-art package.

Stereopsis Only: Validation of a Monocular Depth Cues Reduced Gamified Virtual Reality with Reaction Time Measurement.

The visual depth perception is composed of monocular and binocular depth cues. Studies show that in absence of binocular depth cues the performance of visuomotor tasks like pointing to or grasping objects is limited. Thus, binocular depth cues are of great importance for motor control required in everyday life. However, binocular depth cues like retinal disparity (basis for stereopsis) might be influenced due to developmental disorders of the visual system. For example, amblyopia in which one eye's visual input is not processed leads to loss of stereopsis. The primary amblyopia treatment is occlusion of the healthy eye to force the amblyopic eye to train. However, improvements in stereopsis are poor. Therefore, binocular treatments arose that equilibrate both eyes' visual input to enable binocular vision. However, most approaches rely on divided stimuli which do not account for loss of stereopsis. We created a Virtual Reality (VR) with reduced monocular depth cues in which a stereoscopic task is shown to both eyes simultaneously, consisting of two balls jumping towards the user. One ball appears closer to the user which must be identified. To evaluate the task performance the reaction time is measured. We validated our approach with 18 participants with stereopsis under three contrast settings including one leading to monocular vision. The number of correct responses reduces from 90% under binocular vision to 52% under monocular vision corresponding to random guessing. Our results indicate that it is possible to disable monocular depth cues and create a dynamic stereoscopic task inside a VR.

Hess Screen Revised: How Eye Tracking and Virtual Reality change Strabismus Assessment.

Strabismus is a visual disorder characterized by eye misalignment. The extent of ocular misalignment is denoted as the deviation angle. With the advent of Virtual Reality (VR) Head-Mounted-Displays (HMD) and eye tracking technology, new possibilities measuring strabismus arise. Major research addresses the novel field of VR strabismus assessment by replicating prism cover tests while there is a paucity of research on screen tests. In this work the Hess Screen Test was implemented in VR using a HMD with eye tracking for an objective measurement of the deviation angle. In a study, the functionality was tested and compared with a 2D monitor-based test. The results showed significant differences in the measured deviation angle between the methods. This can be attributed to the type of dissociation of the eyes.