Purpose: Age-related macular degeneration (AMD) is a degenerative condition impacting central vision. Evaluating the effectiveness of low vision devices provides empirical evidence on how devices can rehabilitate and overcome deficits caused by AMD. This evidence could help to facilitate discussion on necessary future improvements to vision enhancement technology.
Methods: A systematic review of the literature was conducted on low vision device use in AMD populations. Relevant peer-reviewed research articles from six databases were screened.
Results: The findings of thirty-five studies revealed a significant positive impact of low vision devices leading to improvements in visual acuity, reading performance, facial recognition, and more. While the studies were found to have moderate risks of bias, a GRADE assessment of the evidence suggested the certainty of the evidence was low-moderate.
Discussion: Simple hand-held low vision devices (e.g., magnifiers) appear to currently have greater preferential support than newer visual enhancement technology (e.g., head mounted devices). Financial, comfort or usability reasons may influence preferences more than performance-based findings. However, there is a lack of studies examining newer technologies in AMD populations, which future research should address. Moreover, given the presence of bias across the studies and limited controlled experiments, confidence in the results may be low.
Conclusions: Most studies indicated that low vision devices have positive impacts on reading and visual performance. But, even though they are reported to be a valuable asset to AMD populations, more rigorous research is required to draw conclusive evidence. IMPLICATIONS FOR REHABILITATIONLow vision devices can improve patient outcomes (e.g., vision, reading ability) for age-related macular degeneration populations.A multidisciplinary combination of low vision devices and rehabilitative services (i.e., eccentric viewing training, counselling, education) may enhance quality of life.
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http://dx.doi.org/10.1080/17483107.2021.1966523 | DOI Listing |
J Intellect Disabil Res
January 2025
Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Background: People with intellectual disabilities (IDs) require more vision care but encounter considerable challenges during eye examinations. Specialised clinics established specifically for people with IDs are generally limited. This study aims to evaluate primary family caregivers' willingness to pay (WTP) for specialised ophthalmology services designed for people with IDs.
View Article and Find Full Text PDFJ Clin Med
December 2024
The David J Apple Center for Vision Research, Department of Ophthalmology, Heidelberg University Eye Clinic, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
This laboratory study aims to assess the effects of misaligning different trifocal intraocular lenses (IOLs) under varying spectral and corneal spherical aberration (SA) conditions. With an IOL metrology device under monochromatic and polychromatic conditions, the following models were studied: AT ELANA 841P, AT LISA Tri 839MP, FineVision HP POD F, Acrysof IQ PanOptix, and Tecnis Synergy ZFR00V. The SA was simulated using an aberration-free and average-SA cornea.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Neurosurgery, University Hospital Leipzig, 04103 Leipzig, Germany.
Sphenoid wing meningiomas (SWM) frequently compress structures of the optic pathway, resulting in significant visual dysfunction characterized by vision loss and visual field deficits, which profoundly impact patients' quality of life (QoL), daily activities, and independence. The objective of this study was to assess the impact of SWM surgery on patient-reported outcome measures (PROMs) regarding postoperative visual function. The Visual Function Score Questionnaire (VFQ-25) is a validated tool designed to assess the impact of visual impairment on quality of life.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three modalities-RGB, thermal, and depth-using datasets collected with infrared array sensors and LiDAR sensors in controlled scenarios and varying resolutions (16 × 12 to 640 × 480) to explore their effectiveness in person identification. Preprocessing techniques, including YOLO-based cropping, were employed to improve subject isolation.
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