Dark adaptation measurement with a mobile device

使用移动设备进行暗适应测量

• 批准号: 10006831
• 负责人: SHRINIVAS PUNDLIK
• 金额: $ 23.82万
• 依托单位: SCHEPENS EYE RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10006831
• 关键词: Adopted; Adoption; Affect; Age; Age Factors; Age related macular degeneration; Agreement; Algorithms; Analysis of Variance; Biological Markers; Blindness; Cellular Phone; Characteristics; Clinic; Clinical; Computer software; Custom; Dark Adaptation; Darkness; Data; Detection; Devices; Disease; Disease Progression; Early Diagnosis; Elderly; Electronics; Environment; Evaluation; Exposure to; Eye; Face; Goals; Health; Health Services Accessibility; Home environment; Impairment; Improve Access; Individual; Lead; Light; Lighting; Measurement; Measures; Methods; Monitor; Outcome; Participant; Patients; Photoreceptors; Population; Populations at Risk; Procedures; Process; Reading; Regression Analysis; Retina; Risk; Screening procedure; Sensitivity and Specificity; Series; Severities; Stimulus; Structure; Test Result; Testing; Time; Validation; Vision; Vision Disorders; Visual Acuity; Work; base; cost; cost effective; effectiveness evaluation; handheld mobile device; image processing; instrument; luminance; novel; response; sample fixation; screening; virtual reality; virtual reality headset; visual stimulus

Project Summary / Abstract In this project we propose to validate a mobile device based dark adaptation measurement method for detection of age-related macular degeneration (AMD). Dark adaptation (DA) is the natural process where our eyes adapt to darkness after being exposed to a bright light. This process of DA is known to be impaired or delayed in people with AMD, even at a very early stage when other vision measures such as visual acuity (VA) are unaltered. Delays in dark adaptation are also correlated with severity of AMD. Thus, DA is a key biomarker of AMD which can be helpful in early detection and even monitoring disease progression. While dedicated clinical devices for DA measurement have been developed, their high cost and limited availability are barriers for adoption of DA testing as part of screening tests for AMD. If a key vision measurement like dark adaptation can be adopted on a consumer electronics platform such as mobile devices, it can be made accessible to a large at-risk population in a cost-effective manner. We have developed a method for mobile device based DA measurement (MOBILE-DA). Subjects sitting in a dark room fixate on a target on the mobile device placed at reading distance, and a series of visual stimuli are presented at a fixed eccentricity with respect to the fixation. The subjects respond to the perceived stimulus by tapping the screen and the device logs the data. Preliminary experimentation suggests that it is feasible to measure DA using contemporary mobile devices. The DA response measured using MOBILE-DA differed significantly between AMD subjects and elderly normal controls, indicating that MOBILE-DA could be sensitive to measuring functional vision changes occurring in AMD. In this project, our main aim is to evaluate the effectiveness of MOBILE-DA in measuring DA characteristics in early/intermediate stage AMD patients with visual acuity 20/40 or better. A significant association of AMD presence on MOBILE-DA characteristics will imply that MOBILE-DA can be potentially used as an early detection tests in clinic. We will compare MOBILE-DA measurements with an existing clinical dark adaptometer device in all study participants for its further validation. We will also compare MOBILE-DA measurements between early and intermediate AMD subject groups to determine whether MOBILE-Da parameters are significantly associated with the severity of AMD. This will impact its potential to be used for monitoring disease progression. The second aim of this project is to develop a custom smartphone virtual reality (VR) googles for deploying MOBILE-DA to obtain better control over measurement conditions by reducing the interference of external lighting conditions and for allowing automated monitoring of fixation stability during the test using the front camera of the smartphones and novel image processing algorithms. We will compare within-subjects the MOBILE-DA measurements with and without smartphone VR googles mode. This study will help us comprehensively evaluate different aspects of MOBILE-DA and its potential to impact AMD screening in the short-term, home-monitoring in AMD patients by enabling self-testing in the long term.

项目概要/摘要 在这个项目中，我们建议验证一种基于移动设备的暗适应测量方法 检测年龄相关性黄斑变性（AMD）。暗适应（DA）是我们的自然过程 眼睛在暴露于强光后会适应黑暗。已知 DA 过程受到损害或 AMD 患者的视力延迟，即使是在早期阶段，此时其他视力指标（例如视力 (VA)） 没有改变。暗适应延迟也与 AMD 的严重程度相关。因此，DA是一个关键的生物标志物 AMD 有助于早期发现甚至监测疾病进展。尽心尽力的同时 用于 DA 测量的临床设备已经开发出来，但其高成本和有限的可用性是障碍 采用 DA 测试作为 AMD 筛选测试的一部分。如果像暗适应这样的关键视力测量 可以在消费电子平台（例如移动设备）上采用，可以供 以具有成本效益的方式帮助大量高危人群。我们开发了一种基于移动设备的 DA 方法 测量（移动-DA）。坐在暗室中的受试者注视放置在移动设备上的目标 阅读距离和一系列视觉刺激以相对于固定的固定偏心率呈现。 受试者通过点击屏幕对感知到的刺激做出反应，设备记录数据。初步的 实验表明，使用现代移动设备测量 DA 是可行的。 DA 使用 MOBILE-DA 测量的 AMD 受试者和正常老年人之间的反应存在显着差异 控制，表明 MOBILE-DA 对测量发生在 AMD。在这个项目中，我们的主要目的是评估 MOBILE-DA 在测量 DA 方面的有效性 视力为20/40或更好的早期/中期AMD患者的特征。一个重要的 AMD 存在与 MOBILE-DA 特性的关联将意味着 MOBILE-DA 可能会 临床上用作早期检测试验。我们将 MOBILE-DA 测量与现有的临床测量进行比较 暗适应计装置在所有研究参与者中进行进一步验证。我们还将比较 MOBILE-DA 早期和中期 AMD 受试者组之间的测量以确定 MOBILE-Da 是否 参数与 AMD 的严重程度显着相关。这将影响其用于 监测疾病进展。该项目的第二个目标是开发定制的智能手机虚拟 现实 (VR) 谷歌部署 MOBILE-DA，以便通过以下方式更好地控制测量条件 减少外部照明条件的干扰并允许自动监控固定 使用智能手机前置摄像头和新颖的图像处理算法进行测试期间的稳定性。我们 将比较受试者内使用和不使用智能手机 VR 谷歌模式时的 MOBILE-DA 测量结果。 这项研究将帮助我们全面评估 MOBILE-DA 的不同方面及其影响潜力 短期进行 AMD 筛查，通过长期自我检测对 AMD 患者进行家庭监测。