Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana, USA.
Department of Communication Sciences and Disorders, Louisiana State University, Baton Rouge, Louisiana, USA.
Brain Behav. 2024 Nov;14(11):e70112. doi: 10.1002/brb3.70112.
BACKGROUND & AIMS: Studies using eye-tracking methodology have made important contributions to the study of language disorders such as aphasia. Nevertheless, in clinical groups especially, eye-tracking studies often include small sample sizes, limiting the generalizability of reported findings. Online, webcam-based tracking offers a potential solution to this issue, but web-based tracking has not been compared with in-lab tracking in past studies and has never been attempted in groups with language impairments.
MATERIALS & METHODS: Patients with post-stroke aphasia (n = 16) and age-matched controls (n = 16) completed identical sentence-picture matching tasks in the lab (using an EyeLink system) and on the web (using WebGazer.js), with the order of sessions counterbalanced. We examined whether web-based eye tracking is as sensitive as in-lab eye tracking in detecting group differences in sentence processing.
Patients were less accurate and slower to respond to all sentence types than controls. Proportions of gazes to the target and foil picture were computed in 100 ms increments, which showed that the two modes of tracking were comparably sensitive to overall group differences across different sentence types. Web tracking showed comparable fluctuations in gaze proportions to target pictures to lab tracking in most analyses, whereas a delay of approximately 500-800 ms appeared in web compared to lab data.
DISCUSSION & CONCLUSIONS: Web-based eye tracking is feasible to study impaired language processing in aphasia and is sensitive enough to detect most group differences between controls and patients. Given that validations of webcam-based tracking are in their infancy and how transformative this method could be to several disciplines, much more testing is warranted.
使用眼动追踪方法的研究为语言障碍(如失语症)的研究做出了重要贡献。然而,在临床群体中,眼动追踪研究通常包括小样本量,限制了报告结果的普遍性。在线、基于网络摄像头的追踪为解决这个问题提供了一种潜在的解决方案,但在过去的研究中,基于网络的追踪并没有与实验室追踪进行比较,而且在语言障碍群体中从未尝试过。
16 名脑卒中后失语症患者和 16 名年龄匹配的对照组在实验室(使用 EyeLink 系统)和网络上(使用 WebGazer.js)完成相同的句子-图片匹配任务,会话顺序进行了平衡。我们检查了基于网络的眼动追踪是否与实验室眼动追踪一样能够敏感地检测句子处理中的组间差异。
与对照组相比,患者对所有句子类型的反应准确性和速度都较低。以 100ms 为增量计算注视目标和干扰图片的比例,结果表明两种追踪模式在不同句子类型上对整体组间差异都具有相当的敏感性。在大多数分析中,网络追踪在注视目标图片的比例波动方面与实验室追踪相当,而与实验室数据相比,网络追踪大约延迟了 500-800ms。
基于网络的眼动追踪可用于研究失语症患者受损的语言处理,并且足够敏感以检测对照组和患者之间的大多数组间差异。鉴于基于网络摄像头的追踪验证仍处于起步阶段,以及这种方法对多个学科的变革性影响,需要进行更多的测试。