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首款基于智能电视的视力测试的开发与验证：一项前瞻性研究。

Development and Validation of the First Smart TV-Based Visual Acuity Test: A Prospective Study.

作者信息

Labiris Georgios, Delibasis Konstantinos, Panagiotopoulou Eirini-Kanella, Pigadas Vassilis, Bakirtzis Minas, Panagis Christos, Dardabounis Doukas, Ntonti Panagiota

机构信息

Department of Ophthalmology, University Hospital of Alexandroupolis, Dragana, 68100 Alexandroupolis, Greece.

Department of Computer Science and Biomedical Informatics, University of Thessaly, 35100 Lamia, Greece.

出版信息

Healthcare (Basel). 2022 Oct 22;10(11):2117. doi: 10.3390/healthcare10112117.

DOI:10.3390/healthcare10112117
PMID:36360458
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9691125/
Abstract

(1) Background: While smartphones are among the primary devices used in telemedical applications, smart TV healthcare apps are not prevalent despite smart TVs' penetrance in home settings. The present study's objective was to develop and validate the first smart TV-based visual acuity (VA) test (Democritus Digital Visual Acuity Test (DDiVAT)) that allows a reliable VA self-assessment. (2) Methods: This is a prospective validation study. DDiVAT introduces several advanced features for reliable VA self-testing; among them: automatic calibration, voice recognition, voice guidance, automatic calculation of VA indexes, and a smart TV-based messaging system. Normal and low vision participants were included in the validation. DDiVAT VA results (VA) were compared against the ones from: (a) the gold-standard conventional ETDRS (VA), and, (b) an independent ophthalmologist who monitored the self-examination testing (VA). Comparisons were performed by noninferiority test (set at 2.5-letters) and intraclass correlation coefficients (ICCs). DDiVAT's test-retest reliability was assessed within a 15-day time-window. (3) Results: A total of 300 participants (185 and 115 with normal and low vision, respectively) responded to ETDRS and DDiVAT. Mean difference in letters was -0.05 for VA-VA, 0.62 for VA-VA, and 0.67 for VA-VA, significantly lower than the 2.5 letter noninferiority margin. ICCs indicated an excellent level of agreement, collectively and for each group (0.922-0.996). All displayed letters in DDiVAT presented a similar difficulty. The overall accuracy of the voice recognition service was 96.01%. ICC for VA test-retest was 0.957. (4) Conclusions: The proposed DDiVAT presented non-significant VA differences with the ETDRS, suggesting that it can be used for accurate VA self-assessment in telemedical settings, both for normal and low-vision patients.

摘要

（1）背景：虽然智能手机是远程医疗应用中的主要设备之一，但尽管智能电视在家用环境中普及率较高，智能电视医疗保健应用却并不普遍。本研究的目的是开发并验证首个基于智能电视的视力（VA）测试（德谟克利特数字视力测试（DDiVAT）），以实现可靠的视力自我评估。（2）方法：这是一项前瞻性验证研究。DDiVAT引入了多项用于可靠视力自我测试的先进功能；其中包括：自动校准、语音识别、语音引导、视力指标自动计算以及基于智能电视的消息系统。验证纳入了正常视力和低视力参与者。将DDiVAT的视力结果（VA）与以下结果进行比较：（a）金标准传统ETDRS的结果（VA），以及（b）一名监测自我检查测试的独立眼科医生的结果（VA）。通过非劣效性测试（设定为2.5个字母）和组内相关系数（ICC）进行比较。在15天的时间窗口内评估DDiVAT的重测信度。（3）结果：共有300名参与者（分别有185名正常视力和115名低视力）接受了ETDRS和DDiVAT测试。VA - VA的字母平均差异为 - 0.05，VA - VA为0.62，VA - VA为0.67，显著低于2.5个字母的非劣效性界限。ICC表明总体及各小组的一致性水平极佳（0.922 - 0.996）。DDiVAT中所有显示的字母难度相似。语音识别服务的总体准确率为96.01%。视力重测的ICC为0.957。（4）结论：所提出的DDiVAT与ETDRS相比，视力差异不显著，这表明它可用于远程医疗环境中正常视力和低视力患者的准确视力自我评估。

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