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SBIR Phase II: Feasibility of a Wearable Blindness Prevention System

SBIR Phase II: Feasibility of a Wearable Blindness Prevention System
SBIR 第二阶段:可穿戴式防盲系统的可行性
批准号:
1951039
负责人:
Joshua Park
金额:
$71.48万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-04-01 至 2023-11-30

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中文摘要
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英文摘要
The broader/commercial impact of this SBIR Phase II project aims to further advance novel wearable technology for glaucoma patients and prepare the technology for broad adoption. Glaucoma, the leading cause of irreversible blindness, has an unknown cause and affects more than 70 million people worldwide. Currently, there is no cure for glaucoma, but early can often save one’s vision. Eye pressure is the most commonly used measure for predicting and monitoring glaucoma. The wearable technology developed under this SBIR project will monitor eye pressure throughout the day and allow clinicians to provide a higher quality of care for at-risk patients. The technology uses photographs to measure how the eye stretches under high pressure. This project aims to adapt the imaging technology into stylish eyeglass frames and develop custom software for converting photographs to eye pressure measurements, informing providers and improving compliance associated with at-home medication. This project aims to advance a novel technology in which wearable eyeglass frames are used to track intraocular pressure (IOP) by imaging the level of pressure-induced mechanical strain associated with the tissue at the front of the eye - specifically, exposed sclera. IOP is, by far, the most commonly used metric for predicting glaucoma, the leading cause of irreversible blindness. In this project, a custom machine learning algorithm will identify characteristic patterns residing in small regions of the scleral images and, by tracking pressure-induced displacement of the regions, calculate IOP. The key objective of Phase II is to accurately measure IOP in real-world conditions with human in-vivo studies, incorporating necessary electronics in the frames. The technology will be further developed in order to improve correlation of the algorithm with conventional IOP captured during the image collection period.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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