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Visual impairment, particularly from glaucoma and retinal dystrophies, significantly hinders mobility and increases the risk of falls, leading to decreased independence and mental health challenges. Current low-vision assistive technologies primarily focus on near-task magnification for reading, leaving a critical gap in tools designed to assist with real-world navigation and peripheral vision loss. To address this, the proposed research evaluates Meta AI glasses, which offer real-time scene narration and object recognition, integrated with the Be My Eyes network. The study hypothesizes that this wearable AI technology will improve ambulation, orientation, and overall quality of life for patients, providing a functional solution for mobility that traditional devices lack.
Full description
Background
Visual impairment, including both low vision and blindness, ranks among the 10 most prevalent causes of disability in North America1. Glaucoma causes irreversible vision loss, and treatments are only available to prevent disease onset and progression, but no cure is available.2. Patients with vision loss have impairments in both physical and mental health, thus limiting their activities of daily living (ADLs).3 In turn, these patients exhibit a decreased quality of life which can result in lowered self-esteem and depression.4,5 In patients with glaucoma, functional loss often begins with glare sensitivity, mobility and difficulty ambulating.5 Due to decreased peripheral vision, patients tend to have an increased risk of accidents and falls. One study found that glaucoma patients walked up to 10% slower than those without glaucoma4. In turn, these patients experienced almost twice as many bumps, stumbles and orientation issues as compared to non-glaucomatous patients.6
Low visual acuity significantly impairs mobility in patients with retinal dystrophies, as it reduces the ability to detect obstacles, navigate unfamiliar environments, and maintain safe ambulation, especially under variable lighting conditions. Performance-based assessments such as the multi-luminance mobility test (MLMT) demonstrate that reduced visual acuity, along with diminished visual field and contrast sensitivity, correlates with slower travel speed, increased collisions, and greater difficulty in orientation and navigation tasks in real-world settings.7,8
Rationale for the Proposed Research
Although a range of low-vision devices is currently available, none are explicitly designed to address mobility as a primary functional outcome. Existing technologies largely target near tasks through optical magnification, providing support for seated reading but offering limited benefit for individuals whose major challenges stem from peripheral visual field loss or real-world navigation difficulties, an unmet need in patients with glaucoma and many inherited retinal disorders.
In contrast, Meta AI glasses represent a new class of wearable assistive technology with capabilities that extend far beyond magnification. These glasses integrate real-time scene narration, environmental description, object recognition, and access to remote human assistance, offering dynamic support across diverse and mobile settings. Their onboard sensors and AI-driven interface also create the possibility of functional visual field assessment and continuous contextual guidance features fundamentally different from traditional low vision devices.
While these devices, known as Meta AI glasses, are gradually becoming more integrated into clinical care, no formal study has yet evaluated their specific impact on mobility in patients with low vision. Understanding whether AI-enhanced wearable devices can improve ambulation, orientation, and functional independence in low vision patients represents an important next step in advancing both clinical practice and patient outcomes.
This proposal aims to evaluate the performance and impact on the quality of life of Meta AI glasses in patients with low vision.
Hypothesis
Use of Meta AI Glasses integrated with the Be My Eyes network will improve mobility and quality of life in patients with low vision.
Objectives
The principal objective of this study is to evaluate the utility of Meta AI Glasses integrated with the Be My Eyes network on mobility in patients with significantly restricted visual fields or low visual acuity.
Specific Aim:
Mobility: To assess whether use of the device improves ambulation, orientation, and navigation safety in real-world .
1. Project design, methodology and analysis This study will be conducted at the Ivey Eye Institute at St. Joseph's Health Care in London, Ontario. Eligible patients with a documented visual field loss will be identified from ophthalmology practices within the institute.
The following inclusion and exclusion criteria will be implemented:
Inclusion criteria:
Exclusion criteria:
5. Has history of stroke with aphasia 6. Has other health condition that would preclude follow-up (e.g., significant malignancy or life-threatening disease) 7. Is unable or unwilling to attend clinic visits required for the study 8. Reports significant loss of vision since last eye exam
Participants will be randomized into two groups:
The randomization will be conducted in a 1:1 ratio to either the intervention group (Meta AI Glasses + Be My Eyes) or the control group (usual low-vision care). Randomization will be performed using a computer-generated sequence with allocation concealment through a centralized system. Outcome assessors and data analysts will remain masked to group assignment, and analyses will follow the intention-to-treat principle.
Enrollment
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Inclusion criteria
Exclusion criteria
5. Has history of stroke with aphasia 6. Has other health condition that would preclude follow-up (e.g., significant malignancy or life-threatening disease) 7. Is unable or unwilling to attend clinic visits required for the study 8. Reports significant loss of vision since last eye exam
Primary purpose
Allocation
Interventional model
Masking
50 participants in 2 patient groups
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Central trial contact
Cindy Hutnik; Monali Malvankar
Data sourced from clinicaltrials.gov
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