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Eye tracking in second language acquisition and bilingualism : a research synthesis and methodological guide
Eye Tracking in Second Language Acquisition and Bilingualism provides foundational knowledge and hands-on advice for designing, conducting, and analysing eye-tracking research in applied linguistics. Godfroid's research synthesis and methodological guide introduces the reader to fundamental facts about eye movements, eye-tracking paradigms for language scientists, data analysis, and the practicalities of building a lab. This indispensable book will appeal to undergraduate students learning principles of experimental design, graduate students developing their theoretical and statistical repertoires, experienced scholars looking to expand their own research, and eye-tracking professionals.
Book
Eye tracking: empirical foundations for a minimal reporting guideline
In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section \"An empirically based minimal reporting guideline\").
Journal Article
Quantitative comparison of a mobile, tablet-based eye-tracker and two stationary, video-based eye-trackers
The analysis of eye movements is a noninvasive, reliable and fast method to detect and quantify brain (dys)function. Here, we investigated the performance of two novel eye-trackers—the Thomas Oculus Motus-research mobile (TOM-rm) and the TOM-research stationary (TOM-rs)—and compared them with the performance of a well-established video-based eye-tracker, i.e., the EyeLink 1000 Plus (EL). The TOM-rm is a fully integrated, tablet-based mobile device that presents visual stimuli and records head-unrestrained eye movements at 30 Hz without additional infrared illumination. The TOM-rs is a stationary, video-based eye-tracker that records eye movements at either high spatial or high temporal resolution. We compared the performance of all three eye-trackers in two different behavioral tasks: pro- and anti-saccade and free viewing. We collected data from 30 human subjects while running all three eye-tracking devices in parallel. Parameters requiring a high spatial or temporal resolution (e.g., saccade latency or gain), as derived from the data, differed significantly between the EL and the TOM-rm in both tasks. Differences between results derived from the TOM-rs and the EL were most likely due to experimental conditions, which could not be optimized for both systems simultaneously. We conclude that the TOM-rm can be used for measuring basic eye-movement parameters, such as the error rate in a typical pro- and anti-saccade task, or the number and position of fixations in a visual foraging task, reliably at comparably low spatial and temporal resolution. The TOM-rs, on the other hand, can provide high-resolution oculomotor data at least on a par with an established reference system.
Journal Article
Noise estimation for head-mounted 3D binocular eye tracking using Pupil Core eye-tracking goggles
Head-mounted, video-based eye tracking is becoming increasingly common and has promise in a range of applications. Here, we provide a practical and systematic assessment of the sources of measurement uncertainty for one such device – the Pupil Core – in three eye-tracking domains: (1) the 2D scene camera image; (2) the physical rotation of the eye relative to the scene camera 3D space; and (3) the external projection of the estimated gaze point location onto the target plane or in relation to world coordinates. We also assess eye camera motion during active tasks relative to the eye and the scene camera, an important consideration as the rigid arrangement of eye and scene camera is essential for proper alignment of the detected gaze. We find that eye camera motion, improper gaze point depth estimation, and erroneous eye models can all lead to added noise that must be considered in the experimental design. Further, while calibration accuracy and precision estimates can help assess data quality in the scene camera image, they may not be reflective of errors and variability in gaze point estimation. These findings support the importance of eye model constancy for comparisons across experimental conditions and suggest additional assessments of data reliability may be warranted for experiments that require the gaze point or measure eye movements relative to the external world.
Journal Article
Online eye tracking and real-time sentence processing: On opportunities and efficacy for capturing psycholinguistic effects of different magnitudes and diversity
Online research methods have the potential to facilitate equitable accessibility to otherwise-expensive research resources, as well as to more diverse populations and language combinations than currently populate our studies. In psycholinguistics specifically, webcam-based eye tracking is emerging as a powerful online tool capable of capturing sentence processing effects in real time. The present paper asks whether webcam-based eye tracking provides the necessary granularity to replicate effects—crucially both large and small—that tracker-based eye tracking has shown. Using the Gorilla Experiment Builder platform, this study set out to replicate two psycholinguistic effects: a robust one, the verb semantic constraint effect, first reported in Altmann and Kamide,
Cognition 73
(3), 247–264 (
1999
), and a smaller one, the lexical interference effect, first examined by Kukona et al.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 40
(2), 326 (
2014
). Webcam-based eye tracking was able to replicate both effects, thus showing that its functionality is not limited to large effects. Moreover, the paper also reports two approaches to computing statistical power and discusses the differences in their outputs. Beyond discussing several important methodological, theoretical, and practical implications, we offer some further technical details and advice on how to implement webcam-based eye-tracking studies. We believe that the advent of webcam-based eye tracking, at least in respect of the visual world paradigm, will kickstart a new wave of more diverse studies with more diverse populations.
Journal Article
Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges
The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.
Journal Article
Assessing the data quality of AdHawk MindLink eye-tracking glasses
Most commercially available eye-tracking devices rely on video cameras and image processing algorithms to track gaze. Despite this, emerging technologies are entering the field, making high-speed, cameraless eye-tracking more accessible. In this study, a series of tests were conducted to compare the data quality of MEMS-based eye-tracking glasses (AdHawk MindLink) with three widely used camera-based eye-tracking devices (EyeLink Portable Duo, Tobii Pro Glasses 2, and SMI Eye Tracking Glasses 2). The data quality measures assessed in these tests included accuracy, precision, data loss, and system latency. The results suggest that, overall, the data quality of the eye-tracking glasses was lower compared to that of a desktop EyeLink Portable Duo eye-tracker. Among the eye-tracking glasses, the accuracy and precision of the MindLink eye-tracking glasses were either higher or on par with those of Tobii Pro Glasses 2 and SMI Eye Tracking Glasses 2. The system latency of MindLink was approximately 9 ms, significantly lower than that of camera-based eye-tracking devices found in VR goggles. These results suggest that the MindLink eye-tracking glasses show promise for research applications where high sampling rates and low latency are preferred.
Journal Article
Evaluating the Tobii Pro Glasses 2 and 3 in static and dynamic conditions
Over the past few decades, there have been significant developments in eye-tracking technology, particularly in the domain of mobile, head-mounted devices. Nevertheless, questions remain regarding the accuracy of these eye-trackers during static and dynamic tasks. In light of this, we evaluated the performance of two widely used devices: Tobii Pro Glasses 2 and Tobii Pro Glasses 3. A total of 36 participants engaged in tasks under three dynamicity conditions. In the “seated with a chinrest” trial, only the eyes could be moved; in the “seated without a chinrest” trial, both the head and the eyes were free to move; and during the walking trial, participants walked along a straight path. During the seated trials, participants’ gaze was directed towards dots on a wall by means of audio instructions, whereas in the walking trial, participants maintained their gaze on a bullseye while walking towards it. Eye-tracker accuracy was determined using computer vision techniques to identify the target within the scene camera image. The findings showed that Tobii 3 outperformed Tobii 2 in terms of accuracy during the walking trials. Moreover, the results suggest that employing a chinrest in the case of head-mounted eye-trackers is counterproductive, as it necessitates larger eye eccentricities for target fixation, thereby compromising accuracy compared to not using a chinrest, which allows for head movement. Lastly, it was found that participants who reported higher workload demonstrated poorer eye-tracking accuracy. The current findings may be useful in the design of experiments that involve head-mounted eye-trackers.
Journal Article