Developmental Neuropsychology, Department of Psychology, Ruhr-University Bochum, Universitätsstr. 150, Bochum, 44801, Germany.
Behav Res Methods. 2018 Apr;50(2):451-465. doi: 10.3758/s13428-017-0913-7.
Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology.
在线实验作为一种可行的替代或补充传统实验室实验的方法，正在认知心理学的许多领域中出现。虽然最近的研究涵盖了基于性能和反应时间的范式，但认知心理学的一种工具到目前为止还没有受到太多关注：眼动追踪。在这项研究中，我们使用了 Papoutsaki 等人最近提供的基于 JavaScript 的眼动追踪算法（国际人工智能联合会议，2016 年）以及消费级网络摄像头，来研究在线眼动追踪的潜力，以利用在线数据传输的常见优势。我们将三种在实验室进行的任务（注视、追踪和自由观看）与在线获取的数据进行了比较，以分析前两种任务的空间精度，以及第三种任务中众所周知的注视模式的可重复性。我们的结果表明，在注视任务中，实验室数据表现出约 172 像素（屏幕尺寸的 15%，3.94°视角）的偏移，而在线数据稍不准确（屏幕尺寸的 18%，207 像素），且显示出更高的方差。在追踪任务中也发现了相同的结果，在刺激运动期间存在恒定的偏移（实验室 211 像素，在线 216 像素）。在自由观看任务中，我们能够复制对眼睛（28.25%）的高度注意力归因，而对其他关键区域（如鼻子（9.71%）和嘴巴（4.00%）的注意力较低。总体而言，我们发现基于网络技术的眼动追踪适用于所有三种任务，并且有信心所需的硬件和软件将不断得到改进，以适应认知心理学中更复杂的实验范式。
