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.

项目总结/摘要 在这个项目中，我们提出了验证一个基于移动终端的暗适应测量方法， 年龄相关性黄斑变性（AMD）的检测。黑暗适应（DA）是一种自然的过程， 暴露在强光下后，眼睛会适应黑暗。已知DA的这一过程受损或 在AMD患者中，即使在其他视力指标（如视力（VA）） 没有改变暗适应的延迟也与AMD的严重程度相关。因此，DA是一种关键的生物标志物， 这可能有助于早期发现，甚至监测疾病进展。虽然致力于 已经开发了用于DA测量的临床设备，它们的高成本和有限的可用性是障碍 采用DA测试作为AMD筛查测试的一部分。如果像暗适应这样的关键视觉测量 可以在诸如移动的设备的消费电子平台上采用， 以具有成本效益的方式为大量高危人群提供服务。我们开发了一种基于移动终端的DA方法 测量（MOBILE-DA）。受试者坐在一个黑暗的房间里注视着一个目标上的移动终端放置在 阅读距离，并且一系列视觉刺激相对于注视以固定的偏心率呈现。 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 实验表明使用当代的移动的设备测量DA是可行的。地方检察官 使用MOBILE-DA测量的反应在AMD受试者和老年正常人之间存在显著差异 对照组，表明MOBILE-DA可以敏感地测量发生在 AMD.在这个项目中，我们的主要目的是评估MOBILE-DA测量DA的有效性 在视力20/40或更好的早期/中期AMD患者中，显著 AMD的存在与MOBILE-DA特征的关联将意味着MOBILE-DA可能是潜在的 在临床上用作早期检测。我们将比较MOBILE-DA测量与现有的临床 在所有研究参与者中使用暗适应仪设备进行进一步验证。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 这些参数与AMD的严重程度显著相关。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一个定制的智能手机虚拟 用于部署MOBILE-DA的虚拟现实（VR）谷歌，以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注视 在使用智能手机的前置摄像头和新颖的图像处理算法的测试过程中的稳定性。我们 将在受试者内比较有和没有智能手机VR谷歌模式的MOBILE-DA测量。 这项研究将帮助我们全面评估移动DA的不同方面及其潜在的影响 短期内进行AMD筛查，长期内通过自我检测对AMD患者进行家庭监测。