Dark adaptation measurement with a mobile device
Dark adaptation measurement with a mobile device
批准号:
10006831
负责人:
SHRINIVAS PUNDLIK
金额:
$23.82万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-30 至 2022-08-31
关键词:
AdoptedAdoptionAffectAgeAge FactorsAge related macular degenerationAgreementAlgorithmsAnalysis of VarianceBiological MarkersBlindnessCellular PhoneCharacteristicsClinicClinicalComputer softwareCustomDark AdaptationDarknessDataDetectionDevicesDiseaseDisease ProgressionEarly DiagnosisElderlyElectronicsEnvironmentEvaluationExposure toEyeFaceGoalsHealthHealth Services AccessibilityHome environmentImpairmentImprove AccessIndividualLeadLightLightingMeasurementMeasuresMethodsMonitorOutcomeParticipantPatientsPhotoreceptorsPopulationPopulations at RiskProceduresProcessReadingRegression AnalysisRetinaRiskScreening procedureSensitivity and SpecificitySeriesSeveritiesStimulusStructureTest ResultTestingTimeValidationVisionVision DisordersVisual AcuityWorkbasecostcost effectiveeffectiveness evaluationhandheld mobile deviceimage processinginstrumentluminancenovelresponsesample fixationscreeningvirtual realityvirtual reality headsetvisual stimulus
中文摘要
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,
眼睛在暴露于强光后适应黑暗。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。
英文摘要
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.
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