Background: The revolutionary technology of smartphone-based retinal imaging has been consistently improving over the years. Smartphone-based retinal image acquisition devices are designed to be portable, easy to use, and cost-efficient, which enables eye care to be more widely accessible especially in geographically remote areas. This enables early disease detection for those who are in low- and middle- income population or just in general has very limited access to eye care. This study investigates the limitation of smartphone compatibility of existing smartphone-based retinal image acquisition devices. Additionally, this study aims to propose a universal adapter design that is usable with an existing smartphone-based retinal image acquisition device known as the PanOptic ophthalmoscope. This study also aims to simulate the reliability, validity, and performance overall of the developed prototype.
Methods: A literature review has been conducted that identifies the limitation of smartphone compatibility among existing smartphone-based retinal image acquisition devices. Designing and modeling of proposed adapter were performed using the software AutoCAD 3D. For the proposed performance evaluation, finite element analysis (FEA) in the software Autodesk Inventor and 5-point scale method were demonstrated.
Results: Published studies demonstrate that most of the existing smartphone-based retinal imaging devices have compatibility limited to specific older smartphone models. This highlights the benefit of a universal adapter in broadening the usability of existing smartphone-based retinal image acquisition devices. A functional universal adapter design has been developed that demonstrates its compatibility with a variety of smartphones regardless of the smartphone dimension or the position of the smartphone's camera lens. The proposed performance evaluation method generates an efficient stress analysis of the proposed adapter design. The end-user survey results show a positive overall performance of the developed universal adapter. However, a significant difference between the expert's views on the developed adapter and the quality of images is observed.
Conclusion: The compatibility of existing smartphone-based retinal imaging devices is still mostly limited to specific smartphone models. Besides this, the concept of a universal and suitable adapter for retinal imaging using the PanOptic ophthalmoscope was presented and validated in this paper. This work provides a platform for future development of smartphone-based ophthalmoscope that is universal.
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http://dx.doi.org/10.1186/s41205-024-00231-0 | DOI Listing |
Biomed Opt Express
November 2024
Department of Biomedical Engineering, University of Illinois Chicago, Chicago, IL 60607, USA.
Widefield fundus photography is critical for the detection, documentation, and management of pediatric eye diseases. Existing clinical pediatric fundus cameras offer a limited field of view (FOV) and suboptimal image contrast, hindering comprehensive peripheral retina examination. Additionally, the high cost and lack of portability of commercial devices restrict their use in resource-limited settings.
View Article and Find Full Text PDFPLOS Digit Health
November 2024
Shahzad Eye Hospital, Karachi, Pakistan.
Background: Diabetic retinopathy (DR) is a leading cause of blindness globally. The gold standard for DR screening is stereoscopic colour fundus photography with tabletop cameras. VistaView is a novel smartphone-based retinal camera which offers mydriatic retinal imaging.
View Article and Find Full Text PDFDiagnostics (Basel)
August 2024
Department of Ophthalmology and Vision Rehabilitation, Medical University of Lodz, 90-549 Lodz, Poland.
Objectives: Despite global research on early detection of age-related macular degeneration (AMD), not enough is being done for large-scale screening. Automated analysis of retinal images captured via smartphone presents a potential solution; however, to our knowledge, such an artificial intelligence (AI) system has not been evaluated. The study aimed to assess the performance of an AI algorithm in detecting referable AMD on images captured on a portable fundus camera.
View Article and Find Full Text PDFIntroduction: Digital exclusion is a growing challenge when deploying digital patient care pathways and a potential barrier to widespread implementation, especially in the field of smartphone-based self-monitoring of vision. This retrospective case series seeks to examine the characteristics of individuals who adhere to a smartphone home monitoring programme using the Alleye app for retinal disease, with a focus on digital exclusion, social deprivation and clinical outcomes.
Methods: We conducted a retrospective analysis of 89 patients with retinal pathologies including diabetic retinopathy and retinal vein occlusions at Moorfields Eye Hospital participating in an Alleye home monitoring programme between April 2020 and November 2022.
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