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Abstract

Virtual reality (VR) and augmented reality (AR) are three-dimensional (3D) environments designed to mimic the real world. They have shown significant applications in science, especially in medicine. Their use spans various areas, including education, surgical training, patient education, and medical instruction. In ophthalmology, which is considered a field of microsurgery, VR and AR provide a 3D environment for practicing precise procedures. The ability to repeat exercises, independence from real patients, and tactile feedback allow residents to practice numerous times in a risk-free setting. Learning in a 3D environment is not limited to surgical techniques but it also supports learning theoretical concepts and practicing patient history-taking, reducing dependence on traditional professional training. This approach allows students in low socioeconomic countries to access high-quality training platforms. Beyond medical education, VR and AR can also be used to educate patients in a simple and accessible way, helping them understand their pathophysiology. Raising awareness about signs and symptoms is an effective method to prevent the progression of eye conditions. In this narrative review, we discuss the applications of VR and AR in ophthalmology, their benefits, and future directions.

Keywords

Virtual reality augmented reality ophthalmology education ophthalmic surgical training

Introduction

Virtual reality (VR) creates a completely virtual environment with no integration of real-world elements. In contrast, augmented reality (AR) is a combination of virtual and real elements, where virtual content is projected onto the real environment. It allows the user to interact with the real world. Applications of VR in medicine vary and include medical education, surgical training, diagnostic imaging, and patient education and care. In ophthalmology, VR and AR can play a valuable role, particularly in surgical training, as these microsurgeries are complex and require a high level of skill and experience. Such a role can be applied in certain areas of a residents’ training, such as globe trauma cases, where the Accreditation Council for Graduate Medical Education minimum is four globe repairs as a primary surgeon. With such requirements, this achievement does not signify competence.¹ Simulators such as the Eyesi Surgical Simulator, a three-dimensional (3D) surgical training system, allow trainees to practice complex procedures in a risk-free environment.

A recent meta-analysis evaluated the effectiveness of the Eyesi Surgical Simulator in ophthalmic training by comparing 108 learners who trained with the simulator to 123 learners who did not. The analysis revealed that those trained with Eyesi experienced significant improvements in technical skills, with a standardized mean difference of 2.02 (95% CI: 1.47–2.57; p < 0.001; I² = 0%). Additionally, the Eyesi group exhibited a notable reduction in technical errors, with an odds ratio of 0.43 (95% CI: 0.20–0.90; p = 0.03; I² = 30%). These findings suggest that incorporating the Eyesi Surgical Simulator into ophthalmic training programs can enhance skill acquisition and reduce errors among trainees.² A prospective cohort evaluation of cataract surgery training showed increased self-confidence in the Eyesi simulator group, which correlated with the total number of tasks completed.³ Given the limitations, such as patient reluctance to be managed by trainees, the risk of complications by residents, the limited availability of suitable training cases, and the varying willingness of experts to transfer their experience, VR-AR-based training represents a new chapter in the transfer of surgical knowledge and skills.⁴ In vitreoretinal surgical training, the evaluation of six modules showed no significant difference between ophthalmology residents and experienced surgeons in two of the modules.⁵ The Eyesi Slit Lamp Simulator, introduced in 2022, allows trainees to examine and diagnose various surface pathologies and practice techniques in a patient- and supervisor-free environment. This presents a valuable opportunity for optometry students and residents to further develop and refine their skills.⁶ Besides surgical training, diagnostic training, such as the strabismus VR diagnostic platform, resulted in improved accuracy and performance scores.⁷ Designing the Virtual Ophthalmology Clinic as a learning tool, rather than relying solely on crowded clinical settings, resulted in a significant improvement of approximately 8% in the experimental group compared to the control group at the 12-month follow-up.⁸

Various settings of VR and AR in surgical training, ophthalmology education/examination, and clinical simulation offer time-saving, cost-effective, and error-reducing benefits, representing a major leap forward in training a more professional healthcare workforce. In this narrative review, we discuss the applications of VR and AR in ophthalmology, their benefits, and future directions.

Methods

A literature search across three databases, using PubMed, Web of Science, and SCOPUS, was performed. All articles published until June 2025 were included in the search. The search strategy utilized a combination of keywords and controlled vocabulary (e.g., MeSH terms) such as “virtual reality,” “augmented reality,” “ophthalmology,” “ophthalmology education,” “surgical training,” “ophthalmic surgery,” “residents,” “ophthalmologists,” “cataract surgery,” “vitreoretinal surgery,” “oculoplastics,” “strabismus,” “amblyopia,” “vision therapy,” “vision rehabilitation,” “simulation,” and “patient education” tailored to each database's syntax.

Abstracts meeting inclusion criteria underwent full-text review by two independent reviewers, with discrepancies resolved through discussion to achieve consensus. Studies that discussed VR or AR in relation to ophthalmology and related subfields (e.g., cataract, retina, and oculoplastics) were included. No initial restrictions were placed on language or publication date. However, primarily English-language articles were ultimately reviewed.

Data extraction focused on simulation type (VR or AR), simulation platform, study design, sample size, application, and relevant findings. Qualitative synthesis was employed to summarize the extracted data, with an emphasis on relevant findings pertaining to their respective sections. Consistent with the narrative review framework, study quality was not formally assessed. The review adhered to the principles of the Declaration of Helsinki.

Applications of VR in ophthalmology

Virtual reality in ophthalmic surgical training

Over the past decade, the integration of VR in ophthalmic surgical training has transitioned from a novel innovation to a cornerstone of contemporary surgical education. By offering immersive, standardized, and repeatable environments, VR platforms are uniquely positioned to mitigate the limitations of traditional apprenticeship-based learning, especially in resource-constrained or ethically sensitive contexts. In this section, we look at how VR technologies shape ophthalmology, are being used in surgeons’ training, and are regarded by experts as effective in teaching new skills.

Cataract surgery

Cataract surgery has led the way for the progress and approval of VR-based courses in ophthalmology. Studies have shown that Eyesi is the leading simulator due to its high construct and predictive validity. In a comparative analysis, Nayer et al. demonstrated that Eyesi performance scores, particularly in capsulorhexis, lens fragmentation, and intraocular lens insertion, correlated with operative proficiency and clearly discriminated between novice and expert users.⁹ These findings were echoed in a Cochrane meta-analysis, which confirmed that simulation-trained residents exhibited both faster surgical times and fewer intraoperative complications compared to traditionally trained counterparts.¹⁰ Studies using Eyesi VR-Based Simulation in Cataract Surgery are summarized in Supplemental Table 1.

Recently, there has been a shift from only reviewing results to also analyzing economic factors. Ng et al. conducted a comparison study that tested how much integrating VR training in regular wet lab sessions benefited residents.¹¹ Those residents who used VR in their training achieved higher International Council of Ophthalmology—Ophthalmology Surgical Competency Assessment Rubric phacoemulsification scores. While the capital cost of VR simulators remained high, their low recurring cost and superior learning outcomes positioned them as a cost-effective investment when evaluated against willingness-to-pay thresholds.

Alternative VR solutions have also been proposed to enhance accessibility. Kaur et al. developed a low-cost, open-source cataract simulator that significantly improved depth perception, instrument control, and procedural flow among junior trainees.¹² These innovations, coupled with frameworks like OntoPhaco, an ontology-driven approach to modular curriculum design, have laid the groundwork for scalable, customizable, and structured VR training pathways.¹³

Manual small incision cataract surgery, often underemphasized in high-resource settings but essential in global ophthalmology, has also benefited from VR innovation. In a multicenter randomized trial, Nair et al. demonstrated that trainees using the HelpMeSee simulator committed significantly fewer critical errors during scleral tunnel creation, validating the simulator's impact on live surgical readiness.¹⁴ During the COVID-19 pandemic, when access to operating rooms was severely restricted, a global survey by Al Hassany et al. confirmed that Eyesi VR sessions were perceived by most ophthalmic surgeons as sufficient to ensure surgical progression.¹⁵ These findings collectively reinforce the dual value of VR as both a skills trainer and a crisis-resilient educational modality.

Vitreoretinal surgery

In posterior segment surgery, where tactile feedback is limited and visual-spatial precision is paramount, VR simulation offers an unparalleled training advantage. RetinaVR, a portable and cost-effective system, has shown promise in differentiating experience levels through tasks such as membrane peeling and forceps manipulation.¹⁶ The simulator not only quantified error rates and task completion time but also reported enhanced trainee confidence, an essential but often underappreciated component of early surgical success.

Additionally, Iskander et al.'s systematic review evaluated validation studies on the use of Eyesi as a training and assessment tool in vitreoretinal surgery. The review reported that vitreoretinal surgeons achieved higher median scores than residents across four Eyesi simulator modules and that residents demonstrated progressive improvement over time in a proficiency-based test.¹⁷ These findings further support that Eyesi vitreoretinal modules consistently exhibit construct validity and facilitate skill transfer to the operating room, reinforcing the role of VR in bridging simulation-based training and clinical performance in retinal surgery. These findings are summarized in Supplemental Table 2.

Oculoplastic and diagnostic training

The scope of VR training has expanded beyond intraocular surgery to include orbital, oculoplastic, and diagnostic techniques. In orbital surgery, Srivatsan et al. demonstrated that VR-enhanced anatomical walkthroughs improved cadaver dissection performance, spatial understanding, and anatomical identification among residents.¹⁸ Similarly, Weiss et al. reported that trainees completing a VR module for endonasal orbital decompression achieved faster procedural times and improved anatomical orientation scores.¹⁹

Virtual reality's role in diagnostic training is exemplified by the Eyesi Indirect ophthalmoscopy simulator. In a randomized trial, Leitritz et al. showed that medical students trained using AR ophthalmoscopy outperformed those taught conventionally in objective assessments and optic disc documentation.²⁰ These findings suggest that simulation may have value not only in training ophthalmic surgeons, but also in raising diagnostic competencies among early learners. This is a critical consideration as ophthalmology continues to receive shrinking curricular space in medical education. These data are also included in Supplemental Table 2.

Educational advantages and emerging role of extended reality

Proven training effectiveness

Extended reality (XR), encompassing VR and AR, has become important for evaluating, acquiring, and refining surgical skills across ophthalmology. Unlike traditional mentorship models, VR platforms provide standardized, data-driven feedback. Metrics such as tool trajectory, tissue interaction scores, and task completion time enable objective benchmarking across learners and institutions.^21,22 These features are particularly valuable in an era of constrained surgical volumes due to duty-hour restrictions, operating room availability, and shifting curricula.

System-level data reinforces these advantages. In a systematic review of 33 surgical trials, Co et al. reported that every study comparing XR to traditional instruction favored XR for performance, engagement, or retention.²³ Within ophthalmology, Muñoz et al. confirmed VR's effectiveness in improving procedural repetition, reducing errors, and building learner confidence, while noting barriers such as simulator cost and limited curricular integration.²¹

Learner engagement

The effectiveness of simulation depends not only on technology but also on learner engagement. Wang et al. showed that trainees entering VR training with positive attitudes, often shaped by gaming or musical backgrounds, achieved superior skill acquisition and responsiveness to feedback on platforms like Eyesi.²⁴ Lu et al. advanced this concept with an eye-tracking–integrated AR system delivering gaze-contingent overlays, reducing cognitive overload and aligning with a broader shift toward personalized, learner-responsive environments.²⁵

Artificial intelligence-enhanced guidance

The merging of artificial intelligence (AI) with VR is augmenting ophthalmic education. Artificial intelligence-enabled tools have been developed that can now provide step-by-step surgical guidance through “smart” operating microscopes and deliver objective feedback from surgical videos, continuously tracking a surgeon's progress.^26–28 Artificial intelligence-driven simulators can also dynamically assess deviations from standard procedures and adjust training intensity to accelerate skill acquisition safely.²⁹ These capabilities are associated with faster surgeries, fewer intraoperative issues, and greater resident confidence.³⁰

Widening scope in diagnostics and therapy

Extended reality is increasingly being applied beyond surgical training to diagnostic and therapeutic settings. Li et al. demonstrated that AR overlays can enhance slit-lamp examinations, integrate real-time OCT interpretations, and guide corneal surgery.³¹ Similarly, Ma et al. highlighted VR's utility in visual field (VF) testing, ocular deviation measurement, and remote perimetry monitoring, signaling XR's emergence as a versatile clinical technology.³² These innovations broaden clinical capabilities while having the potential to enrich resident education.

Supporting its educational value, Kovoor et al. confirmed AR's construct validity and consistent learner benefit.³³ However, as Thomsen et al. cautioned, while simulation studies are growing rapidly, robust evaluations of long-term clinical skill transfer, particularly in ophthalmology, remain limited.³⁴ These findings are summarized in Supplemental Table 3.

Visual field testing using VR

Visual field assessment is fundamental to ophthalmological practice with significant implications for the diagnosis and management of various ocular conditions. Traditional methods for VF assessment, utilizing devices such as the Humphrey Field Analyzer, have established limitations, including patient fatigue, attention variability, and substantial time requirements.³⁵ Virtual reality technology presents a promising alternative approach that addresses these limitations.

Current applications and evidence in VF testing

Virtual reality-based perimetry systems, primarily utilizing head-mounted devices (HMDs), have demonstrated significant potential in clinical evaluations. Multiple comparative studies have assessed the reliability, accuracy, and patient acceptability of VR VF testing against conventional methods.^36,37 Notable among these is the VisuALL platform, a VF testing device utilizing VR, approved by the FDA, created to simulate conventional automated perimeters.³⁸ Research showed significant agreement and correlation between standard clinical methods and VR-based VF assessments in healthy individuals and patients with VF defects, glaucoma, and neuro-ophthalmic disorders.^36,37,39

The immersive nature of VR environments offers distinct advantages in reducing anxiety and improving patient comfort and engagement during testing procedures.⁴⁰ This enhanced testing experience may contribute to more reliable results by reducing the test–retest variability commonly observed in conventional perimetry.⁴¹ Furthermore, the integration of eye tracking technology within VR headsets enables both active VF testing and precise measurement of ocular deviations to ensure proper gaze fixation, providing comprehensive assessment capabilities beyond traditional methods.⁴²

Educational and training VR and AR in VF applications

From an educational perspective, VR-based perimetry systems offer substantial benefits for ophthalmology training programs. These systems enable the simulation of VF testing in controlled virtual environments, allowing trainees to develop proficiency in test administration and interpretation without requiring patient participation or access to specialized equipment. This simulation approach aligns with evidence-based medical education principles, providing hands-on experiential learning in a risk-free setting.⁴³

The training applications extend beyond basic procedural skills. Virtual reality systems can simulate diverse various VF defects associated with pathological conditions such as glaucoma, neurological disorders, and other ocular diseases, enabling trainees to recognize and interpret these conditions effectively. This exposure to varied pathological presentations accelerates the development of pattern recognition skills that would otherwise require extensive clinical experience to acquire.^38,44

Virtual reality perimetry in specific populations, including pediatric patients and those with VF defects, provide valuable insights for trainees.⁴⁰ The data generated from these clinical evaluations not only informs the development of improved testing protocols but also enhances educational content for training future ophthalmologists and technical staff.⁴⁴

Strabismus and amblyopia

Virtual reality enables precise, independent visual input to each eye, making it a valuable tool for diagnosing and treating binocular vision disorders such as strabismus and amblyopia.

Diagnostic training applications in strabismus and amblyopia

The VR training systems employ sophisticated modeling to simulate the clinical environment, allowing trainees to utilize virtual prisms and occluders through haptic interfaces. This high-fidelity simulation recreates the visual presentation of strabismus patients, enabling trainees to develop and refine diagnostic skills without time or space constraints.⁷ The accessibility of these training modules, requiring only a VR headset and controllers, represents a significant advantage over traditional training methods that depend on patient availability and specialized clinical settings.

Recent research has demonstrated significant educational benefits of VR-based training for strabismus diagnosis. In a controlled study, ophthalmology residents who completed a minimum of 30 VR training sessions showed statistically significant improvements in strabismus diagnosis accuracy and in measuring deviation angles when assessing clinical patients. This improvement in diagnostic capabilities is attributed to the realistic simulation offered by VR applications.⁷

Therapeutic applications and training implications

Beyond diagnosis, VR applications for the treatment of binocular vision disorders demonstrate promising outcomes with implications for clinical training. Multiple intervention methodologies have been investigated, including game-based, test-based, simulation-based, and combined approaches.⁴⁵ Among these, game-based interventions have shown particular promise, especially in pediatric populations.⁴⁶

These applications frequently employ theoretical frameworks such as: dichoptic training: presenting different stimuli to each eye to promote binocular integration; vision therapy-based training: using structured exercises to improve binocular coordination; monocular fixation in the binocular field: techniques to address suppression.

Studies evaluating VR-based amblyopia treatment in children have reported improvements in visual acuity (VA) comparable to conventional treatments.⁴⁷ Semi-immersive VR systems, including those utilizing monitors with 3D polarized glasses and dedicated platforms like the I-BiT™ system have demonstrated acceptable compliance rates and positive outcomes in preliminary investigations for the treatment of binocular vision disorders.^48–50

For pediatric strabismus management, VR simulators employing orthopto-diploptics principles and gamification elements have demonstrated statistically significant improvements in VA, as well as reductions in both objective and subjective strabismus angles, when compared to standard treatment protocols. The engaging nature of VR interventions appears to enhance both motivation and compliance, which are critical factors in pediatric vision therapy.⁴⁶

Future directions and educational implications

While current evidence highlights promising applications of VR in treating binocular vision disorders, definitive conclusions regarding its overall effectiveness require additional large-scale clinical trials. Nevertheless, the growing body of literature and consistent preliminary findings indicate VR's significant potential for both clinical application and educational integration.

From medical education perspective, VR simulations of binocular vision disorders provide unprecedented opportunities for experiential learning. Trainees can observe the effects of various interventions in real time, developing a deeper understanding of the principles underlying vision therapy and orthoptics. Furthermore, the ability to manipulate variables within these simulations facilitates hypothesis testing and clinical reasoning development.

The increasing availability of commercial stand-alone VR headsets and smartphone-compatible viewers is reducing implementation barriers, potentially accelerating the integration of these technologies into both clinical practice and ophthalmology training programs. In fact, the American Academy of Ophthalmology recently launched a VR education program. This program, in collaboration with FundamentalVR, aims to improve global eye care.⁴⁷ As research continues to refine these applications, VR is poised to become an essential component of comprehensive education in binocular vision assessment and management.

Vision therapy and rehabilitation

Amblyopia (Lazy Eye) and strabismus training

Conventional methods for treating amblyopia comprise the use of glasses, patching, and penalization with atropine drops or Bangerter filters.⁵¹ In spite of these methods, amblyopia remains prevalent because of factors such as poor access to adequate vision screening programs or inadequate adherence from patients, mainly children, during standard treatment.⁵² In recent years, innovative techniques that involve computerized visual training, like VR, using various types of stimuli have been created and assessed.⁵¹ Virtual reality technologies are efficiently used in optometry and ophthalmology, with the development of VR-based software programs specifically conceived to address various ocular conditions.⁴⁸ These training sessions are supported by research showing the impact of video games on neuromodulatory pathways and the improvement of attention skills fostered by these games, as indicated by neurophysiological studies.⁵³ Compelling progress is on the horizon as various studies have emphasized the potential of VR in clinical medicine, neuro-rehabilitation, and stroke rehabilitation applications. With the continued expansion of complex features such as eye-tracking, haptic feedback, and the versatility of content offered by virtual environments, we can expect groundbreaking refinements in patient care and rehabilitation experiences soon.^54–58

According to Coco-Martin et al., VR proposes a secure setting and can be a practical aid for specific training paradigms focused on visual targets. Nonetheless, the debate over whether VR can complement or potentially supersede conventional therapies is still ongoing.⁵⁹ The recent advancements in clinical practices have enabled healthcare professionals to establish new protocols that incorporate several innovative techniques, including perceptual learning, dichoptic training, and binocular therapy.⁵¹ Perceptual learning involves stimulating the visual pathway using Gabor's stimuli through the repeated practice of visual tasks, which can enhance visual processing.^60–62 By embracing these methods, we can promote an improvement in VA and contrast sensitivity in amblyopic eyes.⁵¹

Visual field expansion in low vision patients

Vision therapy improves VF expansion in low vision patients, mainly those suffering from hemianopia or visual neglect.⁶³ Certain research indicates that vision restoration therapy can lead to slight but significant enhancements in VF detection, although the precise mechanisms and degree of improvement may differ.⁶⁴ Additionally, other methods such as novel VR digital spectacles might play a role in expanding or compensating for the VF.⁶⁵ Nevertheless, experts accept that the demand for visual rehabilitation and creative methods will likely rise soon.

Further research teams commenced to make and scrutinize perimetric and treatment methods for individuals experiencing VF impairments by utilizing VR and mobile technology. The common goal is to employ what are known as “Head Mounted (VR) Devices” and/or mobile applications (using tablets or smartphones) as adequate and trustworthy instruments for both diagnostic and therapeutic objectives.^66–69

A study on visuospatial neglect highlighted the effectiveness of the “Salzburg Visual Field Trainer,” a VR system, in restoring VF loss. Over 254 days, the patient's VF improved by 48.8% in the left eye and 36.8% in the right eye, equating to a visual angle enhancement of 5.5° to 10.5°. Subjectively, there was a 317% improvement in perceived VF functionality, indicating that VR interventions can significantly aid patients with visuospatial neglect.⁶³ Furthermore, a case series evaluated a new image remapping method using VR digital spectacles (DSpecs) to expand the peripheral VF in glaucoma patients, showing that custom monocular VF remapping helped relocate unseen targets. In this study, among 23 patients, 78% identified previously unseen safety hazards with DSpecs. There was a significant progress in recognizing (p = 0.024) and quantifying (p = 0.0026) peripheral objects, indicating that DSpecs enhance peripheral awareness in glaucoma patients.⁶⁴ Virtual reality and AR in vision therapy and rehabilitation are summarized in Supplemental Table 4.

Neuro-visual rehabilitation after stroke or trauma

In neuro-visual rehabilitation, vision therapy (VT) is a tailored treatment plan aimed at enhancing visual abilities and processing following incidents such as strokes or traumatic brain injuries.⁷⁰ VT encompasses a range of individualized neurosensory and neuromuscular activities that are specifically designed and closely monitored to rehabilitate and enhance visual skills and processing. This structured approach aims to improve overall visual function, ensuring optimal outcomes for those undergoing therapy.⁷⁰ A VT program is developed based on the findings from a comprehensive vision assessment and takes into account the outcomes of clinical tests along with the patient's signs and symptoms.⁷⁰ VT might involve the use of lenses, prisms, filters, computer applications, and activities in free space. These exercises can be conducted in the clinic and/or at home but require oversight and monitoring. Reviews of existing research have indicated encouraging results concerning interventions for visuomotor issues following acquired brain injuries.^71–73 However, there is also a recognized need for further research that measures the functional outcomes.

Research and simulation

Simulating visual impairments (e.g., diabetic retinopathy, glaucoma) for research or empathy training

Research on digital vision-impairment simulations has increased in the last decade. There is now substantial work across a variety of hardware and software solutions addressing different conditions and impairments.⁷⁴ Simulating visual impairments through devices like blindfolds or low-vision goggles serves as a valuable resource for both research and empathy training.^75,76 This method enables researchers to examine how individuals perceive and interact with their surroundings without vision. Additionally, it helps educators cultivate understanding and empathy for those with visual impairments.⁷⁴ Empathy training through simulations can significantly enhance awareness of the challenges encountered by individuals with visual impairments, thereby fostering a deeper sensitivity to their needs.^76,77 By experiencing the world from the perspective of a simulated impairment, participants gain a greater understanding of these experiences, which in turn cultivates empathy and compassion.⁷⁴ This approach also enhances interpersonal interactions by equipping individuals with the knowledge and insight required to engage more effectively with those who have visual impairments, promoting inclusion and nurturing positive relationships.⁷⁴

In the study by Jones et al., the effectiveness of VR and AR technologies in simulating the daily challenges experienced by individuals with glaucoma was assessed. This pilot study comprised two tasks that glaucoma patients often find difficult: locating a cell phone in a VR home environment and navigating with visual impairments overlaid in AR. The results demonstrated that these simulated impairments significantly impeded performance in both the VR and AR tasks.⁷⁸ In a more recent advancement, the VisioPainter project introduced 2D authoring software that enables users to create various visual impairments by applying different brush types to simulate distinct views, thereby portraying a range of visual dysfunctions.⁷⁹ While the potential applications of this tool are extensive, the theme of empathy remains a central focus across all the referenced research.

Analyzing eye-tracking and visual perception

Enhancing eye tracking for VR applications generally involves identifying and distinguishing different types of eye movements and utilizing insights about visual and cognitive processes during these movements to achieve the desired results.⁸⁰ Three techniques have been utilized to monitor eye movements in VR systems using HMDs: (1) electro-oculography (EOG), (2) scleral search coils, and the most widely used method, (3) video oculography.⁷⁷ Electro-oculography assesses the positioning of the eye by attaching electrodes to the skin surrounding the eye, which detect the eye's resting electrical potential. These electrodes can be seamlessly integrated into the HMD where they come into contact with the face.^81–84 This method is effective due to the eye's dipole nature, which exhibits a positive charge toward the cornea and a negative charge toward the retina. By placing electrodes on opposite sides of the eye, such as the left and right, we can accurately map the voltage difference, which correlates with the eye's orientation, including its horizontal position.⁸⁵ One limitation of EOG is that it offers a relatively imprecise assessment of eye position. However, it remains the only technique that facilitates tracking when the eyes are closed.⁸⁶

Recent studies have highlighted the advantages of employing eye tracking technology in VR, particularly in areas like interaction and attention monitoring. In their 2019 research, Luro and Sundstedt compared gaze-based targeting in VR with traditional controller methods during a point-and-shoot task. They utilized the System Usability Scale (SUS) and cognitive load questionnaires (NASA TLX) to analyze data collected from various target trajectories and speeds.⁸⁷ The results indicated that gaze can effectively substitute for aiming in VR without compromising task performance or comfort. Participants experienced reduced physical demand when utilizing gaze tracking, and the SUS reflected comparable outcomes for both methods. Additionally, a study conducted by Joo et al. introduced a user interface based on eye tracking, demonstrating a decrease in the time required for simple operations, thereby eliminating the need for dedicated controllers and the associated usage time.⁸⁸ Furthermore, Clay et al. showed the effectiveness of combining eye-tracking with VR to investigate methods and tools applicable in experimentation.⁸⁹

Patient education and communication

Patient education in ophthalmology significantly reduces visual impairment by promoting regular eye screenings, timely diagnoses, and treatment adherence.⁹⁰ A major burden of visual impairment stems from inadequate screening, delayed diagnosis, and treatment noncompliance, often due to limited patient knowledge about eye diseases. Patients who have deeper insight into their condition are more likely to trust their doctors, follow medical advice, adhere to treatment plans, and be actively involved in their healthcare.⁹¹

To improve patients’ education, immersive technologies such as VR and AR are being used to help patients perceive eye symptoms and disease progression in near-realistic conditions. These tools allow patients to better understand how visual impairments affect their daily lives. Simulation tools illustrate that patients often overlook symptom severity and functional deficits during early, unilateral disease stages, emphasizing the risk of silent disease progression if untreated. This further highlights the importance of early diagnosis, regular screenings, follow-up, and timely treatment.^90,92 Virtual reality and AR can enhance patients’ understanding of the anatomical structure of the eye, disease pathophysiology, and the impact of various symptoms deeply. With the help of VR, patients can visualize eye structures in 3D which helps them learn about complicated ophthalmic topics better.^90,92,93 Research demonstrates that both VR and AR effectively educate patients; VR excels in detailed anatomical visualization, whereas AR is especially useful for demonstrating the impact of visual impairments in real-world environments. These technologies can effectively educate patients about eye symptoms such as disability glare, blurred vision, metamorphopsia, perceptual filling-in, and color vision deficits and progression of eye diseases such as glaucoma, cataracts, age-related macular degeneration (AMD), diabetic retinopathy, diabetic macular edema, corneal disorders, refractive errors, color blindness (protanopia), and diplopia. They can also simulate progression of cataract symptoms (blurred vision, reduced contrast sensitivity, dark shadows, and light sensitivity) and AMD-related impairments (contrast loss, visual distortion, and central vision loss), enhancing patient understanding of disease impact.^78,94–98

One study found that 86.7% of patients were willing to use VR or AR to learn more about eye diseases and experience symptoms in a real condition.⁸ Some individuals experienced stress from detailed visuals of anatomy or disease progression; thus, gradual exposure techniques or guided patient counseling could mitigate such reactions.⁹²

In addition to enhancing patient understanding, immersive technologies also improve communication between patients and both their clinicians and healthy individuals. By simulating real-world visual experiences, doctors can better understand what patients are experiencing, while also making clinical explanations more understandable for patients. This shared perspective fosters patient–doctor communication and supports the concept of informed decision-making.⁹³

Additionally, the potential of VR and AR extends beyond patient education into early screening applications, further expanding their utility in preventive ophthalmic care. They can help detect early signs of cataracts, contrast sensitivity changes, refractive errors, and glaucoma in individuals who may not yet show symptoms. This application opens new possibilities for preventive eye care, helping to diminish the long-term burden of vision loss.⁹⁹

Three-dimensional simulations enable patients to visualize eye surgeries such as cataract extraction and vitrectomy, clearly presenting surgical anatomy, procedural steps, instrument usage, and anticipated visual outcomes, thus enhancing patient comprehension and reducing anxiety. Making complex ophthalmic surgeries more understandable and visualizable can enhance the likelihood of informed consent and adherence to treatment. In this way, patients can have realistic expectations regarding surgery outcomes and recovery trends.^21,100

For older adults, who suffer from age-related eye problems more often, these technologies are very helpful as they show the progression of symptoms and the importance of regular eye exams. Augmented reality systems can simulate central vision loss in AMD, blurred vision in cataracts, peripheral vision loss in glaucoma, and patchy VFs in diabetic retinopathy at varying levels of severity. This could encourage elderly individuals, who constitute a significant portion of the population with eye diseases, to engage in regular screenings and follow-ups.¹⁰¹ The applications and outcomes of VR and AR in patient education are summarized in Supplemental Table 5.

Benefits of VR in ophthalmology, challenges, limitations, and future perspectives

Virtual reality is a valuable tool with applications in various areas, including surgical training and simulation, diagnosis and screening, patient education, rehabilitation, tele-ophthalmology, and remote monitoring. It is particularly useful in surgical training, especially for procedures such as cataract surgery and vitreoretinal operations.²

In the future, advancements in realistic, immersive environments, real-time feedback, and skill assessment are expected to enhance ophthalmic training. These improvements will reduce reliance on live patients and help alleviate the stress trainees experience due to potential complications arising from limited surgical experience.⁴

Training is not limited to surgical procedures. It also includes learning theoretical knowledge, conducting clinical examinations, and practicing patient history-taking.⁶ Studying ocular anatomy and complications, as well as simulating pathologies that may occur unpredictably in clinical settings, can be effectively visualized in a 3D virtual environment.¹⁰²

When it comes to taking patient histories, VR allows students to practice communication skills in a stress-free setting, giving them the opportunity to repeat the process multiple times until they become confident and professional.⁸

Moreover, students can experience medical training in realistic clinical scenarios, rather than relying solely on theoretical information from textbooks. In this way, large volumes of textbook content can be transformed into a virtual format, eliminating the need for physical space like libraries. On the other hand, it can be easier for professionals to share their perspectives in education more accurately and effectively, especially with those who may not have access to high-level educators or training opportunities. Imagine being at home and seeing the professor in a 3D environment, explaining complex concepts.¹⁰³ Although the lack of interaction between students and the trainer is a limitation, this method can save time and energy for both trainees and trainers.

Although this 3D virtual training environment offers many educational benefits, studying medicine is not just about acquiring knowledge. It is also a valuable opportunity for juniors to learn from the personal experiences and perspectives of professionals, something that could be entirely lost in the future.^104,105

Virtual reality-based diagnostic tools offer affordable, portable, and user-friendly assessments that can enhance the diagnosis and monitoring of diseases. They are especially valuable in underserved areas where access to specialists is limited.¹⁰⁶ For example, in slit lamp examinations, the combination of AI and VR can improve the accuracy of assessments by enabling more precise algorithm-based analysis.⁶ In this context, diseases such as glaucoma, AMD, and diabetic retinopathy can be monitored remotely, allowing for early detection before the condition worsens.

Beyond diagnosis, training, and monitoring, 3D virtual tools for patient education, including disease interpretation and medication guidance, can improve patient compliance during the treatment period.⁹¹

Despite the many advantages and promising capabilities of VR and AR technologies, they are also accompanied by several limitations. The high cost of technology makes these tools not readily accessible, especially in underresourced or low-income regions.^107,108 Many of these simulation models also lack the fine details and normal range of physiologic variability seen in real patients.^108,109 Other device limitations, such as reduced depth perception, visual lags, lack of tactile feedback, and limited personal interactions can further hinder trainees from translating these nuanced skills into real-world outcomes and patients from being fully engaged with educational, diagnostic, and rehabilitative VR tools.^108,110 Further studies are needed to identify methods of addressing these limitations.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251387047 - Supplemental material for Virtual reality and augmented reality in ophthalmology: A recent update

Supplemental material, sj-docx-1-dhj-10.1177_20552076251387047 for Virtual reality and augmented reality in ophthalmology: A recent update by Zahra Bibak-Bejandi, Alireza Razavi, Hanieh Niktinat, Zarife Jale Yucel, Aron M Sebhat, Reyhaneh Bibak-Bejandi, Zohre Arabpour, Anwar N Khandaker, Jaron Sanchez, Omar Nusair and Mohammad Soleimani in DIGITAL HEALTH

Supplemental Material

sj-docx-2-dhj-10.1177_20552076251387047 - Supplemental material for Virtual reality and augmented reality in ophthalmology: A recent update

Supplemental material, sj-docx-2-dhj-10.1177_20552076251387047 for Virtual reality and augmented reality in ophthalmology: A recent update by Zahra Bibak-Bejandi, Alireza Razavi, Hanieh Niktinat, Zarife Jale Yucel, Aron M Sebhat, Reyhaneh Bibak-Bejandi, Zohre Arabpour, Anwar N Khandaker, Jaron Sanchez, Omar Nusair and Mohammad Soleimani in DIGITAL HEALTH

Supplemental Material

sj-docx-3-dhj-10.1177_20552076251387047 - Supplemental material for Virtual reality and augmented reality in ophthalmology: A recent update

Supplemental material, sj-docx-3-dhj-10.1177_20552076251387047 for Virtual reality and augmented reality in ophthalmology: A recent update by Zahra Bibak-Bejandi, Alireza Razavi, Hanieh Niktinat, Zarife Jale Yucel, Aron M Sebhat, Reyhaneh Bibak-Bejandi, Zohre Arabpour, Anwar N Khandaker, Jaron Sanchez, Omar Nusair and Mohammad Soleimani in DIGITAL HEALTH

Supplemental Material

sj-docx-4-dhj-10.1177_20552076251387047 - Supplemental material for Virtual reality and augmented reality in ophthalmology: A recent update

Supplemental material, sj-docx-4-dhj-10.1177_20552076251387047 for Virtual reality and augmented reality in ophthalmology: A recent update by Zahra Bibak-Bejandi, Alireza Razavi, Hanieh Niktinat, Zarife Jale Yucel, Aron M Sebhat, Reyhaneh Bibak-Bejandi, Zohre Arabpour, Anwar N Khandaker, Jaron Sanchez, Omar Nusair and Mohammad Soleimani in DIGITAL HEALTH

Supplemental Material

sj-docx-5-dhj-10.1177_20552076251387047 - Supplemental material for Virtual reality and augmented reality in ophthalmology: A recent update

Supplemental material, sj-docx-5-dhj-10.1177_20552076251387047 for Virtual reality and augmented reality in ophthalmology: A recent update by Zahra Bibak-Bejandi, Alireza Razavi, Hanieh Niktinat, Zarife Jale Yucel, Aron M Sebhat, Reyhaneh Bibak-Bejandi, Zohre Arabpour, Anwar N Khandaker, Jaron Sanchez, Omar Nusair and Mohammad Soleimani in DIGITAL HEALTH

Footnotes

ORCID iDs

Alireza Razavi

Aron M Sebhat

Jaron Sanchez

Omar Nusair

Mohammad Soleimani

Ethical Considerations:

This article does not contain any studies with human or animal participants.

Consent to Participate:

This article does not contain any studies with human or animal participants.

Contributorship:

Zahra Bibak-Bejandi contributed to project administration,methodology,investigation,conceptualization,visualization,and writing—original draft;Alireza Razavi contributed to writing—review & editing,investigation,and visualization;Hanieh Niktinat contributed to writing—review & editing,investigation,and visualization;Zarife Jale Yucel contributed to writing—review & editing,investigation,visualization;Aron M. Sebhat contributed to writing—review & editing,investigation,and visualization;Reyhaneh Bibak-Bejandi contributed to writing—review & editing,investigation,and visualization;Zohre Arabpour contributed to writing—review & editing,investigation,and visualization;Anwar N Khandaker contributed to writing—review & editing,investigation,and visualization;Jaron Sanchez contributed to writing—review & editing and investigation;Omar Nusair contributed to writing—review & editing and investigation;Mohammad Soleimani contributed to writing—review & editing,supervision,project administration,methodology,and investigation.

Funding:

The authors received no financial support for the research,authorship,and/or publication of this article.

Declaration of Conflicting Interests:

The authors declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Data Availability:

The original contributions presented in the study are included in the article,further inquiries can be directed to the corresponding authors.

Supplemental Material:

Supplemental material for this article is available online.

References

Justin

, et al. The Ophthalmology Surgical Competency Assessment Rubric (OSCAR) for open globe surgical management. Clin Ophthalmol 2022; 16: 2041–2046.

Carr

, et al. Effectiveness of the eyesi surgical simulator for ophthalmology trainees: systematic review and meta-analysis. Can J Ophthalmol 2024; 59: 172–180.

Wisse

, et al. The eyesi simulator in training ophthalmology residents: results of a pilot study on self-efficacy, motivation and performance. BMJ Simul Technol Enhanc Learn 2017; 3: 111–115.

Alfawaz

. Ophthalmology resident surgical training: can we do better? Saudi J Ophthalmol 2019; 33: 159–162.

Cissé

, et al. EYESI Surgical simulator: validity evidence of the vitreoretinal modules. Acta Ophthalmol 2019; 97: e277–e282.

Jaud

, et al. Eyesi surgical simulator: validation of a proficiency-based test for assessment of vitreoretinal surgical skills. Acta Ophthalmol 2021; 99: 390–396.

Moon

, et al. Usefulness of virtual reality-based training to diagnose strabismus. Sci Rep 2021; 11: 5891.

Succar

, et al. The impact of the virtual ophthalmology clinic on medical students’ learning: a randomised controlled trial. Eye (Lond) 2013; 27: 1151–1157.

Nayer

, et al. Predictive and construct validity of virtual reality cataract surgery simulators. J Cataract Refract Surg 2020; 46: 907–912.

10.

Lin

, et al. Virtual reality training for cataract surgery operating performance in ophthalmology trainees. Cochrane Database Syst Rev 2021; 12: CD014953.

11.

, et al. Cost-effectiveness of virtual reality and wet laboratory cataract surgery simulation. Medicine (Baltimore) 2023; 102: e35067.

12.

Kaur

, et al. Cost-effective and adaptable cataract surgery simulation with basic technology. Eye 2022; 36: 1384–1389.

13.

Youcef

, et al. OntoPhaco: an ontology for virtual reality training in ophthalmology domain—a case study of cataract surgery. IEEE Access 2021; 9: 152347–78.

14.

Nair

, et al. Effectiveness of simulation-based training for manual small incision cataract surgery among novice surgeons: a randomized controlled trial. Sci Rep 2021; 11: 10945.

15.

Al Hassany

. Use of the eyesi virtual reality simulator during and after the COVID-19 pandemic and its relevance to phaco-emulsification surgery future training planning. J Surg Simul 2024; 11: 62–69.

16.

Antaki

, et al. Democratizing vitreoretinal surgery training with a portable and affordable virtual reality simulator in the metaverse. Transl Vis Sci Technol 2024; 13: 5.

17.

Iskander

, et al. Virtual reality and augmented reality in ophthalmology: a contemporary prospective. Asia Pac J Ophthalmol (Phila) 2021; 10: 244–252.

18.

Srivatsan

, et al. Trainee experience in virtual reality simulation in orbital surgery. Orbit 2025; 44: 274–280.

19.

Weiss

, et al. Endoscopic endonasal surgery simulator as a training tool for ophthalmology residents. Ophtalmic Plast Reconstr Surg 2008; 24: 460–464.

20.

Leitritz

, et al. Critical evaluation of the usability of augmented reality ophthalmoscopy for the training of inexperienced examiners. Retina 2014; 34: 785–791.

21.

Muñoz

, et al. Augmented reality, virtual reality, and game technologies in ophthalmology training. Information 2022; 13: 222.

22.

Dubinski

, et al. Enhancing surgical education for medical students through virtual reality: the digital surgical operating theatre tour. World Neurosurg 2025; 194: 123523.

23.

, et al. Extended reality in surgical education: a systematic review. Surgery 2023; 174: 1175–1183.

24.

Wang

, et al. Immersive teaching using virtual reality technology to improve ophthalmic surgical skills for medical postgraduate students. Postgrad Med 2024; 136: 487–495.

25.

, et al. Integrating eye-tracking to augmented reality system for surgical training. J Med Syst 2020; 44: 192.

26.

Mishra

, et al. Artificial intelligence and ophthalmic surgery. Curr Opin Ophthalmol 2021; 32: 425–430.

27.

Ahuja

, et al. The utility of virtual reality in ophthalmology: a review. Clin Ophthalmol 2025; 19: 1683–1692.

28.

Koucheki

, et al. Integrating artificial intelligence and virtual reality in orthopedic surgery: a comprehensive review. HSS J 2025; 21: 289–298.

29.

Bakshi

, et al. The era of artificial intelligence and virtual reality: transforming surgical education in ophthalmology. Br J Ophthalmol 2021; 105: 1325–1328.

30.

Gyldenkerne

, et al. Impact on binocular visual function of small-incision lenticule extraction for high myopia. J Cataract Refract Surg 2021; 47: 430–438.

31.

, et al. Augmented reality in ophthalmology: applications and challenges. Front Med (Lausanne) 2021; 8: 733241.

32.

MKI

, et al. Virtual reality and augmented reality—emerging screening and diagnostic techniques in ophthalmology: a systematic review. Surv Ophthalmol 2022; 67: 1516–1530.

33.

Kovoor

, et al. Validity and effectiveness of augmented reality in surgical education: a systematic review. Surgery 2021; 170: 88–98.

34.

Thomsen

ASS

, et al. Update on simulation-based surgical training and assessment in ophthalmology: a systematic review. Ophthalmology 2015; 122: 1111–30.e1.

35.

Tsapakis

, et al. Visual field examination method using virtual reality glasses compared with the Humphrey perimeter. Clin Ophthalmol 2017; 11: 1431–1443.

36.

Soans

, et al. Patients prefer a virtual reality approach over a similarly performing screen-based approach for continuous oculomotor-based screening of glaucomatous and neuro-ophthalmological visual field defects. Front Neurosci 2021; 15: 745355.

37.

McLaughlin

, et al. Reliability of visual field testing in a telehealth setting using a head-mounted device: a pilot study. J Glaucoma 2024; 33: 15–23.

38.

Montelongo

, et al. A virtual reality-based automated perimeter, device, and pilot study. Transl Vis Sci Technol 2021; 10: 20–20.

39.

Stapelfeldt

, et al. Virtual reality–based and conventional visual field examination comparison in healthy and glaucoma patients. Transl Vis Sci Technol 2021; 10: 10–10.

40.

Mesfin

, et al. Pilot study comparing a new virtual reality–based visual field test to standard perimetry in children. J AAPOS 2024; 28: 103933.

41.

Greenfield

, et al. Virtual reality oculokinetic perimetry test reproducibility and relationship to conventional perimetry and OCT. Ophthalmol Sci 2021; 2: 100105.

42.

Sethi

, et al.

Exploring head-mounted virtual visual fields for glaucoma: how do they stack up against Humphrey tests?

TNOA J Ophthalmic Sci Res 2024; 62: 301–310.

43.

Pottle

. Virtual reality and the transformation of medical education. Future Healthc J 2019; 6: 181–185.

44.

Cabrera

, et al. Virtual reality in residents training. Ann Eye Sci 2019; 4: 27.

45.

Halicka

, et al. Virtual reality visual training in an adult patient with anisometropic amblyopia: visual and functional magnetic resonance outcomes. Vision (Basel) 2021; 5: 22.

46.

Obukhov

, et al. Medical VR simulator for pediatric strabismus treatment. Technologies 2024; 12: 228.

47.

American Academy of Ophthalmology . Academy Launches Virtual Reality Education Program [Internet]. San Francisco: American Academy of Ophthalmology, 2024 Feb 29 [cited 2025 Aug 5], Available from: https://www.aao.org/newsroom/news-releases/detail/academy-launches-vr-education-program.

48.

Chan

, et al. Design and assessment of amblyopia, strabismus, and myopia treatment and vision training using virtual reality. Digit Health 2023; 9: 20552076231176638.

49.

Rajavi

, et al. The role of interactive binocular treatment system in amblyopia therapy. J Curr Ophthalmol 2016; 28: 217–222.

50.

Waddingham

, et al. Preliminary results from the use of the novel Interactive Binocular Treatment (I-BiT™) system, in the treatment of strabismic and anisometropic amblyopia. Eye (Lond) 2006; 20: 375–378.

51.

Hernández-Rodríguez

, et al. Active vision therapy for anisometropic amblyopia in children: a systematic review. J Ophthalmol 2020; 2020: 4282316.

52.

Tailor

, et al. Binocular versus standard occlusion or blurring treatment for unilateral amblyopia in children aged three to eight years. Cochrane Database Syst Rev 2022; 2: CD011347.

53.

Dye

, et al. The development of attention skills in action video game players. Neuropsychologia 2009; 47: 1780–1789.

54.

Wohlgenannt

, et al. Virtual reality. Bus Inf Syst Eng 2020; 62: 455–461.

55.

Zhao

, et al.

Virtual reality: a possible approach to myopia prevention and control?

Med Hypotheses 2018; 121: 1–3.

56.

Žiak

, et al. Amblyopia treatment of adults with dichoptic training using the virtual reality oculus rift head mounted display: preliminary results. BMC Ophthalmol 2017; 17: 105.

57.

Fong

, et al. Task-specific virtual reality training on hemiparetic upper extremity in patients with stroke. Virtual Real 2022; 26: 453–464.

58.

Tang

, et al. Application of virtual reality (VR) technology for medical practitioners in type and screen (T&S) training. J Comput Assist Learn 2021; 37: 359–369.

59.

Coco-Martin

, et al. The potential of virtual reality for inducing neuroplasticity in children with amblyopia. J Ophthalmol 2020; 2020: 7067846.

60.

Birch

. Amblyopia and binocular vision. Prog Retin Eye Res 2013; 33: 67–84.

61.

Dosher

, et al. Visual perceptual learning and models. Annu Rev Vis Sci 2017; 3: 343–363.

62.

Levi

, et al. Perceptual learning as a potential treatment for amblyopia: a mini-review. Vision Res 2009; 49: 2535–2549.

63.

Leitner

, et al. Visual field improvement in neglect after virtual reality intervention: a single-case study. Neurocase 2021; 27: 308–318.

64.

Sayed

, et al. Expansion of peripheral visual field with novel virtual reality digital spectacles. Am J Ophthalmol 2020; 210: 125–135.

65.

Marshall

, et al. Visual field expansion after visual restoration therapy. Clin Rehabil 2010; 24: 1027–1035.

66.

Goh

, et al. Objective assessment of activity limitation in glaucoma with smartphone virtual reality goggles: a pilot study. Transl Vis Sci Technol 2018; 7: 10.

67.

Leitner

, et al. Salzburg visual field trainer (SVFT): a virtual reality device for (the evaluation of) neuropsychological rehabilitation. PLoS One 2021; 16: e0249762.

68.

Matsumoto

, et al. Visual field testing with head-mounted perimeter ‘imo’. PLoS One 2016; 11: e0161974.

69.

Wroblewski

, et al. Testing of visual field with virtual reality goggles in manual and visual grasp modes. Biomed Res Int 2014; 2014: 206082.

70.

Johansson

, et al. Vision therapy as part of neurorehabilitation after acquired brain injury–a clinical study in an outpatient setting. Brain Inj 2021; 35: 82–89.

71.

Riggs

, et al. Visual deficit interventions in adult stroke and brain injury: a systematic review. Am J Phys Med Rehabil 2007; 86: 853–860.

72.

Pollock

, et al. Interventions for disorders of eye movement in patients with stroke. Cochrane Database Syst Rev 2011; 2011: CD008389.

73.

Simpson-Jones

, et al. Vision rehabilitation interventions following mild traumatic brain injury: a scoping review. Disabil Rehabil 2019; 41: 2206–2222.

74.

Krösl

, et al. Exploring the educational value and impact of vision-impairment simulations on sympathy and empathy with XREye. Multimodal Technol Interact 2023; 7: 70.

75.

Apple

, et al. The artificial reduction of visual cues as a means of preparing training programs for low vision clients. Low Vis Abstr 1976; 2: 4–6.

76.

Bozeman

. Central field loss in object-system and low-vision simulation. Bull Spec Educ 2006; 2006: 207–220.

77.

Zwoliński

, et al. Visual impairments simulation in virtual reality as an empathy booster. Virtual Real 2025; 29: 75.

78.

Jones

, et al. Seeing other perspectives: evaluating the use of virtual and augmented reality to simulate visual impairments (OpenVisSim). NPJ Digit Med 2020; 3: 32.

79.

Maeda

, et al. VisionPainter: Authoring experience of visual impairment in virtual reality. In: International Conference on Human-Computer Interaction. Springer, 2022.

80.

Holmqvist

, et al. Eye Tracking: A Comprehensive Guide to Methods and Measures. Oxford: Oxford University Press, 2011.

81.

Bulling

, et al. Wearable EOG goggles: seamless sensing and context-awareness in everyday environments. J Ambient Intell Smart Environ 2009; 1: 157–171.

82.

Shimizu

, et al. Eye movement interactions in google cardboard using a low cost EOG setup. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, Heidelberg, Germany, 12–16 September 2016. New York, NY: Association for Computing Machinery.

83.

Adhanom

, et al. Gazemetrics: an open-source tool for measuring the data quality of HMD-based eye trackers. Proc Eye Track Res Appl Symp 2020; 2020: 19.

84.

Kumar

, et al. Electrooculogram-based virtual reality game control using blink detection and gaze calibration. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2016.

85.

Mowrer

, et al. The corneo-retinal potential difference as the basis of the galvanometric method of recording eye movements. Am J Physiol-Legacy Content 1935; 114: 423–428.

86.

Adhanom

, et al. Eye tracking in virtual reality: a broad review of applications and challenges. Virtual Real 2023; 27: 1481–1505.

87.

Luro

, et al. A comparative study of eye tracking and hand controller for aiming tasks in virtual reality. In: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications. 2019.

88.

Joo

, et al. A study on eye-tracking-based interface for VR/AR education platform. Multimedia Tools Appl 2020; 79: 16719–16730.

89.

Clay

, et al. Eye tracking in virtual reality. J Eye Mov Res 2019; 12.

90.

Huang

, et al. Lack of awareness of common eye conditions in the community. Ophthalmic Epidemiol 2013; 20: 52–60.

91.

Osterberg

, et al. Adherence to medication. N Engl J Med 2005; 353: 487–497.

92.

van der Kruk

, et al. Virtual reality as a patient education tool in healthcare: a scoping review. Patient Educ Couns 2022; 105: 1928–1942.

93.

Lam

AKN

, et al. Use of virtual reality simulation to identify vision-related disability in patients with glaucoma. JAMA Ophthalmol 2020; 138: 490–498.

94.

, et al. Augmented reality in ophthalmology: applications and challenges. Front Med (Lausanne) 2021; 8: 733241.

95.

Krösl

, et al. ICthroughVR: Illuminating cataracts through virtual reality. In: 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, 23–27 March 2019, pp.655–663. IEEE.

96.

Krösl

, et al. CatARact: Simulating cataracts in augmented reality. In: 2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2020.

97.

Ates

, et al. Immersive simulation of visual impairments using a wearable see-through display. In: Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction. Association for Computing Machinery. Stanford, California, USA, 2015, pp.225–228.

98.

Jones

, et al. Degraded reality: Using VR/AR to simulate visual impairments. 2018 IEEE Workshop on Augmented and Virtual Realities for Good (VAR4Good). 2018.

99.

MKI

, et al. Virtual reality and augmented reality—emerging screening and diagnostic techniques in ophthalmology: a systematic review. Surv Ophthalmol 2022; 67: 1516–1530.

100.

Erdag

, et al. Augmented and virtual reality in retinal care: a systematic review of their role in training, surgery, and treatment. Surv Ophthalmol 2025; S0039-6257: 00072–4.

101.

Hung

, et al. The interactive use of augmented reality for educating the elderly on common age-related eye disease. BMC Geriatr 2025; 25: 6.

102.

Nakai

, et al. Anatomy education for medical students in a virtual reality workspace: a pilot study. Clin Anat 2022; 35: 40–44.

103.

Ukrani

, et al. Low-cost peer-taught virtual research workshops for medical students in Pakistan: a creative, scalable, and sustainable solution for student research. BMC Med Educ 2021; 21: 557.

104.

Kodama

, et al. Effects of collaborative training using virtual co-embodiment on motor skill learning. IEEE Trans Vis Comput Graph 2023; 29: 2304–2314.

105.

Zhang

, et al. One body, but four hands": exploring the role of virtual hands in virtual co-embodiment. IEEE Trans Vis Comput Graph 2025; 31: 3634–3644.

106.

Obst

, et al. AI-enhanced 3D models in global virtual reality case conferences for surgical care in a low-income country: exploratory study. JMIR Form Res 2025; 9: e69300.

107.

Please

, et al. Virtual reality technology for surgical learning: qualitative outcomes of the first virtual reality training course for emergency and essential surgery delivered by a UK-Uganda partnership. BMJ Open Qual 2024; 13: e002477.

108.

Baniasadi

, et al. Challenges and practical considerations in applying virtual reality in medical education and treatment. Oman Med J 2020; 35: e125.

109.

Mergen

, et al. Reviewing the current state of virtual reality integration in medical education - a scoping review. BMC Med Educ 2024; 24: 788.

110.

Laspro

, et al. The use of virtual reality in surgical training: implications for education, patient safety, and global health equity. Surgeries 2023; 4: 635–646.

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