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.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
SCREENING
Masking
NONE
Enrollment
98
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.
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.
NYU Langone Health
New York, New York, United States
Average time to complete the trial
Time frame: 1 Day of Intervention
Average number of obstacle collisions during the trial
Time frame: 1 Day of Intervention
Average travel time
Time frame: 1 Day of Intervention
Average distance traveled by the participant
Time frame: 1 Day of Intervention
Preferred walking speed
Time frame: 1 Day of Intervention
Orientation
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.
Time frame: 1 Day of Intervention
Number of instances in which the participant stop for more than 2 seconds
Time frame: 1 Day of Intervention
Total time spent during stops of more than 2 seconds
Time frame: 1 Day of Intervention
Average time it takes to understand how to interact with the system and run the simulation of the bus ride
Time frame: 1 Day of Intervention
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