Age-Related Macular Degeneration, Diabetic Retinopathy, Glaucoma, Visual Impairment
Conditions
Brief summary
In this study, the study team utilize virtual reality (VR) to simulate visual impairments of different types and severity in healthy subjects. The platform implements three of the most widespread forms of visual impairment in the United States (US): age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma, each with three levels of severity, (mild, moderate, and severe). At present, glaucoma is further developed toward a multidimensional visual impairment simulation. The platform is utilized: i) to provide a safe, controllable, and repeatable set of environments for development and preliminary testing of electronic travel aids (ETAs) in a variety of conditions (i.e., using the ETA to navigate in the immersed environment); and ii) to equip blind and low vision (BVI) professionals, inclusive of orientation and mobility (O&M) instructors, with a controlled, tunable training platform for skill/capacity building, assessment, and refinement of O&M techniques, as well as visually impaired trainees with a safe and immersive environment to improve their O&M skills and learn novel techniques. Two sets of hypothesis-driven experiments are proposed to assess the feasibility of the platform with respect to these two objectives.
Interventions
OTHERIn-House Developed VR Platform - AMD, DR, Glaucoma
Participants will conduct experiments using commercial VR headsets and controllers. Visual impairments will be systematically simulated in VR. There are three visual impairment simulations (AMD, DR, and glaucoma) at three levels of severity (mild, moderate, or severe). Symptoms' simulation tools include a gaussian blur shader, distortion shader, and a culling mask with a gray spot in the middle.
OTHERIn-House Developed VR Platform - Glaucoma
In the second set of experiments, a multidimensional visual impairment simulation of a single pathology (glaucoma) will be used at three levels of severity (mild, moderate, or severe). The post-processing package to simulate includes glare, difficulty in light, change adaptation, ambient occlusion, visual clutter, and overall blurred effect. The shader graph package will be used to create a distortion localized on assets surfaces only.
Sponsors
NYU Langone Health
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
Yes
Inclusion criteria
(patients with visual impairment) 1. Aged 18-80; 2. People with glaucoma of all different levels and etiologies. Inclusion Criteria (healthy controls) 1. Aged 18-80; 2. Gender neutral: male or female.
Exclusion criteria
(patients with visual impairment & healthy controls) 1. Significant cognitive dysfunction (score \<24 on Folsteins' Mini Mental Status Examination) 2. Previous neurological illness or psychiatric disorders, or suffer from a heart condition or other serious medical conditions 3. Significant mobility restrictions; people using walkers and wheelchairs 4. Pregnancy 5. Elderly 6. Seizures (people who previously have had a seizure, loss of awareness, or other symptom linked to an epileptic condition) 7. Interference with medical devices (the headset and controller(s) may contain magnets or components that emit radio waves, which could affect the operation of nearby electronics, including cardiac pacemakers, hearing aids, and defibrillators)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Average time to complete the trial | 1 Day of Intervention | — |
| Average number of obstacle collisions during the trial | 1 Day of Intervention | — |
| Average travel time | 1 Day of Intervention | — |
| Average distance traveled by the participant | 1 Day of Intervention | — |
| Preferred walking speed | 1 Day of Intervention | — |
| Orientation | 1 Day of Intervention | Orientation is measured through the time average of a polarization index, measured as the cosin of the angle between the direction of the instantaneous velocity vector and the straight line linking the instantaneous position of the participant and the following waypoint. |
| Number of instances in which the participant stop for more than 2 seconds | 1 Day of Intervention | — |
| Total time spent during stops of more than 2 seconds | 1 Day of Intervention | — |
| Average time it takes to understand how to interact with the system and run the simulation of the bus ride | 1 Day of Intervention | — |
Countries
United States
Outcome results
None listed