使用阶梯扫频刺激,通过光动眼震自动估算视力。

Jason Turuwhenua, Mohammad Norouzifard, Zaw LinTun, Misty Edmonds, Rebecca Findlay, Joanna Black, Benjamin Thompson
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引用次数: 0

摘要

目的:对于有认知障碍的成年人和幼儿来说,测量视敏度(VA)是一项挑战。我们开发了一套使用眼球震颤(OKN)测量视力的自动系统。方法:单眼测量健康参与者(23 人,年龄 30±12 岁)的 VA-OKN 和 ETDRS(VA-ETDRS)视力。每只眼睛的视力分为减弱(22 人,>0.2 logMAR)和未减弱(24 人,≤0.2 logMAR)。VA-OKN 刺激是一个漂移(5 度/秒)消失盘阵列,以大小递减/递增的顺序呈现(0.0 至 1.0 logMAR,以 0.1 logMAR 为步长)。刺激物每 2 秒钟扫描一次,每只眼睛扫描 10 次。眼动跟踪数据可确定 OKN 活动何时停止(下降扫描)或开始(上升扫描),从而得出自动扫描 VA。扫视轨迹由一名对 VA-ETDRS 一无所知的评审员进行随机化和评估。由此确定最终的每次扫查 VA 和 VA-OPN。结果:使用随机选取的单眼进行分析。视力损失组:总体平均 VA-OKN 和 VA-ETDRS 之间无明显差异(p>0.05,配对 t 检验),r2 统计量为 0.84。95% 的一致性界限为 0.19 logMAR。无视力障碍组:VA-OKN 和 VA-ETDRS 之间存在 0.24 logMAR 的偏差,且未发现相关性(r2 = 0.06)。然而,分类的总体敏感性/特异性为 100%。结论:VA-ETDRS 和 VA-OKN 之间存在稳健的相关性。该方法能正确检测出 VA 缺陷。
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Automated visual acuity estimation by optokinetic nystagmus using a stepped sweep stimulus.
Purpose: Measuring visual acuity (VA) can be challenging in adults with cognitive impairment and young children. We developed an automatic system for measuring VA using Optokinetic Nystagmus (OKN). Methods: VA-OKN and VA by ETDRS (VA-ETDRS) were measured monocularly in healthy participants (n=23, age 30±12). VA was classified as reduced (n=22, >0.2 logMAR) or not (n=24, ≤0.2 logMAR) in each eye. VA-OKN stimulus was an array of drifting (5 deg/sec) vanishing disks presented in descending/ascending size order (0.0 to 1.0 logMAR in 0.1 logMAR steps). The stimulus was stepped every 2 seconds, and 10 sweeps were shown per eye. Eye tracking data determined when OKN activity ceased (descending sweep) or began (ascending sweep) to give an automated sweep VA. Sweep traces were randomized and assessed by a reviewer blinded to VA-ETDRS. A final per sweep VA and VA-OKN was thereby determined. Results: A single randomly selected eye was used for analysis. VA deficit group: There was no significant difference between overall mean VA-OKN and VA-ETDRS (p>0.05, paired t-test) and the r2 statistic was 0.84. The 95% limits of agreement were 0.19 logMAR. No VA deficit group: There was a 0.24 logMAR bias between VA-OKN and VA-ETDRS and no correlation was found (r2 = 0.06). However, the overall sensitivity/specificity for classification was 100%. Conclusions: A robust correlation between VA-ETDRS and VA-OKN was found. The method correctly detected a VA deficit.
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