The impact of slippage on the data quality of head-worn eye trackers

Visual fixation patterns to AAC displays are significantly correlated with motor selection for individuals with Down syndrome or individuals on the autism spectrum

Eye tracking research technologies are often used to study how individuals attend visually to different types of AAC displays (e.g. visual scene displays, grid displays). The assumption is that efficiency of visual search may relate to efficiency of motor selection necessary for communication via aided AAC; however, this assumption has not received direct empirical study. We examined the relation between speed of visual search and speed of motor selection of symbols. Ten individuals on the autism spectrum (AS; Study 1) and nine with Down syndrome (DS; Study 2) participated in a search task using simulated AAC displays with a main visual scene display (VSD) and a navigation bar of thumbnail VSDs. Participants were given an auditory prompt to find one of four thumbnail VSDs in the navigation bar. Eye tracking technologies measured how long it took participants to fixate visually on the thumbnail VSD, and recorded how long it took participants to select the thumbnail VSD with a finger. A statistically significant relationship emerged between visual fixation and selection latencies, confirming the positive relationship between visual processing and motor selection for both groups of participants. Eye tracking data may serve as a useful proxy measure for evaluating how display design influences selection of AAC symbols, especially when individuals are unwilling or unable to comply with traditional behaviorally-based assessment tasks.

Cognitive load in tele-robotic surgery: a comparison of eye tracker designs

PURPOSE

Eye gaze tracking and pupillometry are evolving areas within the field of tele-robotic surgery, particularly in the context of estimating cognitive load (CL). However, this is a recent field, and current solutions for gaze and pupil tracking in robotic surgery require assessment. Considering the necessity of stable pupillometry signals for reliable cognitive load estimation, we compare the accuracy of three eye trackers, including head and console-mounted designs.

METHODS

We conducted a user study with the da Vinci Research Kit (dVRK), to compare the three designs. We collected eye tracking and dVRK video data while participants observed nine markers distributed over the dVRK screen. We compute and analyze pupil detection stability and gaze prediction accuracy for the three designs.

RESULTS

Head-worn devices present better stability and accuracy of gaze prediction and pupil detection compared to console-mounted systems. Tracking stability along the field of view varies between trackers, with gaze predictions detected at invalid zones of the image with high confidence.

CONCLUSION

While head-worn solutions show benefits in confidence and stability, our results demonstrate the need to improve eye tacker performance regarding pupil detection, stability, and gaze accuracy in tele-robotic scenarios.

Improving Eye-Tracking Data Quality: A Framework for Reproducible Evaluation of Detection Algorithms

High-quality eye-tracking data are crucial in behavioral sciences and medicine. Even with a solid understanding of the literature, selecting the most suitable algorithm for a specific research project poses a challenge. Empowering applied researchers to choose the best-fitting detector for their research needs is the primary contribution of this paper. We developed a framework to systematically assess and compare the effectiveness of 13 state-of-the-art algorithms through a unified application interface. Hence, we more than double the number of algorithms that are currently usable within a single software package and allow researchers to identify the best-suited algorithm for a given scientific setup. Our framework validation on retrospective data underscores its suitability for algorithm selection. Through a detailed and reproducible step-by-step workflow, we hope to contribute towards significantly improved data quality in scientific experiments.

Influence of autistic traits and communication role on eye contact behavior during face-to-face interaction

Eye contact is a central component in face-to-face interactions. It is important in structuring communicative exchanges and offers critical insights into others' interests and intentions. To better understand eye contact in face-to-face interactions, we applied a novel, non-intrusive deep-learning-based dual-camera system and investigated associations between eye contact and autistic traits as well as self-reported eye contact discomfort during a referential communication task, where participants and the experimenter had to guess, in turn, a word known by the other individual. Corroborating previous research, we found that participants' eye gaze and mutual eye contact were inversely related to autistic traits. In addition, our findings revealed different behaviors depending on the role in the dyad: listening and guessing were associated with increased eye contact compared with describing words. In the listening and guessing condition, only a subgroup who reported eye contact discomfort had a lower amount of eye gaze and eye contact. When describing words, higher autistic traits were associated with reduced eye gaze and eye contact. Our data indicate that eye contact is inversely associated with autistic traits when describing words, and that eye gaze is modulated by the communicative role in a conversation.

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data

We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using only synthetic data has the benefit of completely sidestepping the time-consuming process of manual annotation that is required for supervised training on real eye images. To systematically evaluate the accuracy of our method, we first tested it on images with synthetic CRs placed on different backgrounds and embedded in varying levels of noise. Second, we tested the method on two datasets consisting of high-quality videos captured from real eyes. Our method outperformed state-of-the-art algorithmic methods on real eye images with a 3-41.5% reduction in terms of spatial precision across data sets, and performed on par with state-of-the-art on synthetic images in terms of spatial accuracy. We conclude that our method provides a precise method for CR center localization and provides a solution to the data availability problem, which is one of the important common roadblocks in the development of deep learning models for gaze estimation. Due to the superior CR center localization and ease of application, our method has the potential to improve the accuracy and precision of CR-based eye trackers.

GlassesValidator: A data quality tool for eye tracking glasses

According to the proposal for a minimum reporting guideline for an eye tracking study by Holmqvist et al. (2022), the accuracy (in degrees) of eye tracking data should be reported. Currently, there is no easy way to determine accuracy for wearable eye tracking recordings. To enable determining the accuracy quickly and easily, we have produced a simple validation procedure using a printable poster and accompanying Python software. We tested the poster and procedure with 61 participants using one wearable eye tracker. In addition, the software was tested with six different wearable eye trackers. We found that the validation procedure can be administered within a minute per participant and provides measures of accuracy and precision. Calculating the eye-tracking data quality measures can be done offline on a simple computer and requires no advanced computer skills.

Are depressive symptoms linked to a reduced pupillary response to novel positive information?-An eye tracking proof-of-concept study

Introduction

Depressive symptoms have been linked to difficulties in revising established negative beliefs in response to novel positive information. Recent predictive processing accounts have suggested that this bias in belief updating may be related to a blunted processing of positive prediction errors at the neural level. In this proof-of-concept study, pupil dilation in response to unexpected positive emotional information was examined as a psychophysiological marker of an attenuated processing of positive prediction errors associated with depressive symptoms.

Methods

Participants (N = 34) completed a modified version of the emotional Bias Against Disconfirmatory Evidence (BADE) task in which scenarios initially suggest negative interpretations that are later either confirmed or disconfirmed by additional information. Pupil dilation in response to the confirmatory and disconfirmatory information was recorded.

Results

Behavioral results showed that depressive symptoms were related to difficulties in revising negative interpretations despite disconfirmatory positive information. The eye tracking results pointed to a reduced pupil response to unexpected positive information among people with elevated depressive symptoms.

Discussion

Altogether, the present study demonstrates that the adapted emotional BADE task can be appropriate for examining psychophysiological aspects such as changes in pupil size along with behavioral responses. Furthermore, the results suggest that depression may be characterized by deviations in both behavioral (i.e., reduced updating of negative beliefs) and psychophysiological (i.e., decreased pupil dilation) responses to unexpected positive information. Future work should focus on a larger sample including clinically depressed patients to further explore these findings.

Assessing Visual Avoidance of Faces During Real-Life Social Stress in Children with Social Anxiety Disorder: A Mobile Eye-Tracking Study

This study measured visual attention (fixation count, dwell time) during two real-life social stress tasks using mobile eye-tracking glasses in children (9-13 years) diagnosed with social anxiety disorder (SAD; n = 25) and a healthy control group (HC; n = 30). The influence of state anxiety on attention allocation and negative self-evaluation biases regarding gaze behavior were also examined. Compared to the HC group, children with SAD showed visual avoidance (i.e., fewer fixations) of the faces of interaction partners during the second social stress task. While visual avoidance in HC children decreased with declining state anxiety from the first to the second social stress task, no such effect was found in children with SAD. A negative self-evaluation bias regarding gaze behavior in children with SAD was not found. In sum, measuring visual attention during real-life social situations may help enhance our understanding of social attention in childhood SAD.

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.

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.

How robust are wearable eye trackers to slow and fast head and body movements?

How well can modern wearable eye trackers cope with head and body movement? To investigate this question, we asked four participants to stand still, walk, skip, and jump while fixating a static physical target in space. We did this for six different eye trackers. All the eye trackers were capable of recording gaze during the most dynamic episodes (skipping and jumping). The accuracy became worse as movement got wilder. During skipping and jumping, the biggest error was 5.8∘. However, most errors were smaller than 3∘. We discuss the implications of decreased accuracy in the context of different research scenarios.

Infant embodied attention in context: Feasibility of home-based head-mounted eye tracking in early infancy

Social communication emerges from dynamic, embodied social interactions during which infants coordinate attention to caregivers and objects. Yet many studies of infant attention are constrained to a laboratory setting, neglecting how attention is nested within social contexts where caregivers dynamically scaffold infant behavior in real time. This study evaluates the feasibility and acceptability of the novel use of head-mounted eye tracking (HMET) in the home with N = 40 infants aged 4 and 8 months who are typically developing and at an elevated genetic liability for autism spectrum disorder (ASD). Results suggest that HMET with young infants with limited independent motor abilities and at an elevated likelihood for atypical development is highly feasible and deemed acceptable by caregivers. Feasibility and acceptability did not differ by age or ASD likelihood. Data quality was also acceptable, albeit with younger infants showing slightly lower accuracy, allowing for preliminary analysis of developmental trends in infant gaze behavior. This study provides new evidence for the feasibility of using in-home HMET with young infants during a critical developmental period when more complex interactions with the environment and social partners are emerging. Future research can apply this technology to illuminate atypical developmental trajectories of embodied social attention in infancy.

Pathways for Naturalistic Looking Behavior in Primate I: Behavioral Characteristics and Brainstem Circuits

Organisms control their visual worlds by moving their eyes, heads, and bodies. This control of "gaze" or "looking" is key to survival and intelligence, but our investigation of the underlying neural mechanisms in natural conditions is hindered by technical limitations. Recent advances have enabled measurement of both brain and behavior in freely moving animals in complex environments, expanding on historical head-fixed laboratory investigations. We juxtapose looking behavior as traditionally measured in the laboratory against looking behavior in naturalistic conditions, finding that behavior changes when animals are free to move or when stimuli have depth or sound. We specifically focus on the brainstem circuits driving gaze shifts and gaze stabilization. The overarching goal of this review is to reconcile historical understanding of the differential neural circuits for different "classes" of gaze shift with two inconvenient truths. (1) "classes" of gaze behavior are artificial. (2) The neural circuits historically identified to control each "class" of behavior do not operate in isolation during natural behavior. Instead, multiple pathways combine adaptively and non-linearly depending on individual experience. While the neural circuits for reflexive and voluntary gaze behaviors traverse somewhat independent brainstem and spinal cord circuits, both can be modulated by feedback, meaning that most gaze behaviors are learned rather than hardcoded. Despite this flexibility, there are broadly enumerable neural pathways commonly adopted among primate gaze systems. Parallel pathways which carry simultaneous evolutionary and homeostatic drives converge in superior colliculus, a layered midbrain structure which integrates and relays these volitional signals to brainstem gaze-control circuits.

Webcam eye tracking close to laboratory standards: Comparing a new webcam-based system and the EyeLink 1000

This paper aims to compare a new webcam-based eye-tracking system, integrated into the Labvanced platform for online experiments, to a "gold standard" lab-based eye tracker (EyeLink 1000 - SR Research). Specifically, we simultaneously recorded data with both eye trackers in five different tasks, analyzing their real-time performance. These tasks were a subset of a standardized test battery for eye trackers, including a Large Grid task, Smooth Pursuit eye movements, viewing natural images, and two Head Movements tasks (roll, yaw). The results show that the webcam-based system achieved an overall accuracy of 1.4°, and a precision of 1.1° (standard deviation (SD) across subjects), an error of about 0.5° larger than the EyeLink system. Interestingly, both accuracy (1.3°) and precision (0.9°) were slightly better for centrally presented targets, the region of interest in many psychophysical experiments. Remarkably, the correlation of raw gaze samples between the EyeLink and webcam-based was at about 90% for the Large Grid task and about 80% for Free View and Smooth Pursuit. Overall, these results put the performance of the webcam-based system roughly on par with mobile eye-tracking devices (Ehinger et al. PeerJ, 7, e7086, 2019; Tonsen et al., 2020) and demonstrate substantial improvement compared to existing webcam eye-tracking solutions (Papoutsaki et al., 2017).

A toolkit for wide-screen dynamic area of interest measurements using the Pupil Labs Core Eye Tracker

Eye tracking measurements taken while watching a wide field screen are challenging to perform. Commercially available remote eye trackers typically do not measure more than 35 degrees in eccentricity. Analysis software was developed using the Pupil Core Eye Tracking data to analyze viewing behavior under circumstances as natural as possible, on a 1.55-m-wide screen allowing free head movements. Additionally, dynamic area of interest (AOI) analyses were performed on data of participants viewing traffic scenes. A toolkit was created including software for simple allocation of dynamic AOIs (semi-automatically and manually), measurement of parameters such as dwell times and time to first entry, and overlaying gaze and AOIs on video. Participants (n =11) were asked to look at 13 dynamic AOIs in traffic scenes from appearance to disappearance in order to validate the setup and software. Different AOI margins were explored for the included objects. The median ratio between total appearance time and dwell time was about 90% for most objects when appropriate margins were chosen. This validated open-source toolkit is readily available for researchers who want to perform dynamic AOI analyses with the Pupil Core eye tracker, especially when measurements are desired on a wide screen, in various fields such as psychology, transportation, and low vision research.

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.

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.

Minimal reporting guideline for research involving eye tracking (2023 edition)

A guideline is proposed that comprises the minimum items to be reported in research studies involving an eye tracker and human or non-human primate participant(s). This guideline was developed over a 3-year period using a consensus-based process via an open invitation to the international eye tracking community. This guideline will be reviewed at maximum intervals of 4 years.

Visual Search Strategies of Elite Fencers: An Exploratory Study in Ecological Competitive Situation

This study investigates the visual activity of fencers in conditions resembling official competitions. Previous research in experimental conditions has shown that experts focus on specific areas of the torso and the armed arm to control movement initiation. Eight right-handed fencers (epee: two males, one female; foil: one male; sabre: two males, two females) participated in a simulated competition, wearing an eye tracker during one bout. The findings showed that the main fixation in foil and sabre is the upper torso, while in epee, it is the lower torso. In epee and sabre, the upper torso is viewed about 50% of the time, with three other areas also observed, while in foil, the fixation is totally directed to the upper torso. Additionally, two new areas of interest were identified: the score machine and an area involving fixations other than the opponent. The study found no direct link between visual activity and performance. The visual search strategy varies among weapons, with foil using a gaze anchor or foveal spot and epee and sabre utilizing a visual pivot due to the discipline's inherent rules. The study also emphasizes that competition-like conditions can disrupt visual activity with external stimuli, possibly affecting performance.

Effectiveness of a time to fixate for fitness to drive evaluation in neurological patients

We present a method to automatically calculate time to fixate (TTF) from the eye-tracker data in subjects with neurological impairment using a driving simulator. TTF presents the time interval for a person to notice the stimulus from its first occurrence. Precisely, we measured the time since the children started to cross the street until the drivers directed their look to the children. From 108 neurological patients recruited for the study, the analysis of TTF was performed in 56 patients to assess fit-, unfit-, and conditionally-fit-to-drive patients. The results showed that the proposed method based on the YOLO (you only look once) object detector is efficient for computing TTFs from the eye-tracker data. We obtained discriminative results for fit-to-drive patients by application of Tukey's honest significant difference post hoc test (p < 0.01), while no difference was observed between conditionally-fit and unfit-to-drive groups (p = 0.542). Moreover, we show that time-to-collision (TTC), initial gaze distance (IGD) from pedestrians, and speed at the hazard onset did not influence the result, while the only significant interaction is among fitness, IGD, and TTC on TTF. Obtained TTFs are also compared with the perception response times (PRT) calculated independently from eye-tracker data and YOLO. Although we reached statistically significant results that speak in favor of possible method application for assessment of fitness to drive, we provide detailed directions for future driving simulation-based evaluation and propose processing workflow to secure reliable TTF calculation and its possible application in for example psychology and neuroscience.

Highly reproducible eyeblink timing during formula car driving

How do humans blink while driving a vehicle? Although gaze control patterns have been previously reported in relation to successful steering, eyeblinks that disrupt vision are believed to be randomly distributed during driving or are ignored. Herein, we demonstrate that eyeblink timing shows reproducible patterns during real formula car racing driving and is related to car control. We studied three top-level racing drivers. Their eyeblinks and driving behavior were acquired during practice sessions. The results revealed that the drivers blinked at surprisingly similar positions on the courses. We identified three factors underlying the eyeblink patterns: the driver's individual blink count, lap pace associated with how strictly they followed their pattern on each lap, and car acceleration associated with when/where to blink at a moment. These findings suggest that the eyeblink pattern reflected cognitive states during in-the-wild driving and experts appear to change such cognitive states continuously and dynamically.

Eye-tracking technology and the dynamics of natural gaze behavior in sports: an update 2016-2022

Updating and complementing a previous review on eye-tracking technology and the dynamics of natural gaze behavior in sports, this short review focuses on the progress concerning researched sports tasks, applied methods of gaze data collection and analysis as well as derived gaze measures for the time interval of 2016-2022. To that end, a systematic review according to the PRISMA guidelines was conducted, searching Web of Science, PubMed Central, SPORTDiscus, and ScienceDirect for the keywords: eye tracking, gaze behavio*r, eye movement, and visual search. Thirty-one studies were identified for the review. On the one hand, a generally increased research interest and a wider area of researched sports with a particular increase in official's gaze behavior were diagnosed. On the other hand, a general lack of progress concerning sample sizes, amounts of trials, employed eye-tracking technology and gaze analysis procedures must be acknowledged. Nevertheless, first attempts to automated gaze-cue-allocations (GCA) in mobile eye-tracking studies were seen, potentially enhancing objectivity, and alleviating the burden of manual workload inherently associated with conventional gaze analyses. Reinforcing the claims of the previous review, this review concludes by describing four distinct technological approaches to automating GCA, some of which are specifically suited to tackle the validity and generalizability issues associated with the current limitations of mobile eye-tracking studies on natural gaze behavior in sports.

How to improve data quality in dog eye tracking

Pupil-corneal reflection (P-CR) eye tracking has gained a prominent role in studying dog visual cognition, despite methodological challenges that often lead to lower-quality data than when recording from humans. In the current study, we investigated if and how the morphology of dogs might interfere with tracking of P-CR systems, and to what extent such interference, possibly in combination with dog-unique eye-movement characteristics, may undermine data quality and affect eye-movement classification when processed through algorithms. For this aim, we have conducted an eye-tracking experiment with dogs and humans, and investigated incidences of tracking interference, compared how they blinked, and examined how differential quality of dog and human data affected the detection and classification of eye-movement events. Our results show that the morphology of dogs' face and eye can interfere with tracking methods of the systems, and dogs blink less often but their blinks are longer. Importantly, the lower quality of dog data lead to larger differences in how two different event detection algorithms classified fixations, indicating that the results of key dependent variables are more susceptible to choice of algorithm in dog than human data. Further, two measures of the Nyström & Holmqvist (Behavior Research Methods, 42(4), 188-204, 2010) algorithm showed that dog fixations are less stable and dog data have more trials with extreme levels of noise. Our findings call for analyses better adjusted to the characteristics of dog eye-tracking data, and our recommendations help future dog eye-tracking studies acquire quality data to enable robust comparisons of visual cognition between dogs and humans.

A novel end-to-end dual-camera system for eye gaze synchrony assessment in face-to-face interaction

Quantification of face-to-face interaction can provide highly relevant information in cognitive and psychological science research. Current commercial glint-dependent solutions suffer from several disadvantages and limitations when applied in face-to-face interaction, including data loss, parallax errors, the inconvenience and distracting effect of wearables, and/or the need for several cameras to capture each person. Here we present a novel eye-tracking solution, consisting of a dual-camera system used in conjunction with an individually optimized deep learning approach that aims to overcome some of these limitations. Our data show that this system can accurately classify gaze location within different areas of the face of two interlocutors, and capture subtle differences in interpersonal gaze synchrony between two individuals during a (semi-)naturalistic face-to-face interaction.

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").

Advances in Materials, Sensors, and Integrated Systems for Monitoring Eye Movements

Eye movements show primary responses that reflect humans' voluntary intention and conscious selection. Because visual perception is one of the fundamental sensory interactions in the brain, eye movements contain critical information regarding physical/psychological health, perception, intention, and preference. With the advancement of wearable device technologies, the performance of monitoring eye tracking has been significantly improved. It also has led to myriad applications for assisting and augmenting human activities. Among them, electrooculograms, measured by skin-mounted electrodes, have been widely used to track eye motions accurately. In addition, eye trackers that detect reflected optical signals offer alternative ways without using wearable sensors. This paper outlines a systematic summary of the latest research on various materials, sensors, and integrated systems for monitoring eye movements and enabling human-machine interfaces. Specifically, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, sensor functions, systems' performances, and their applications in eye tracking. Finally, we discuss the remaining challenges and suggest research directions for future studies.

Weighted Pointer: Error-aware Gaze-based Interaction through Fallback Modalities

Gaze-based interaction is a fast and ergonomic type of hands-free interaction that is often used with augmented and virtual reality when pointing at targets. Such interaction, however, can be cumbersome whenever user, tracking, or environmental factors cause eye tracking errors. Recent research has suggested that fallback modalities could be leveraged to ensure stable interaction irrespective of the current level of eye tracking error. This work thus presents Weighted Pointer interaction, a collection of error-aware pointing techniques that determine whether pointing should be performed by gaze, a fallback modality, or a combination of the two, depending on the level of eye tracking error that is present. These techniques enable users to accurately point at targets when eye tracking is accurate and inaccurate. A virtual reality target selection study demonstrated that Weighted Pointer techniques were more performant and preferred over techniques that required the use of manual modality switching.

Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures

Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1–6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions.

Eye contact avoidance in crowds: A large wearable eye-tracking study

Eye contact is essential for human interactions. We investigated whether humans are able to avoid eye contact while navigating crowds. At a science festival, we fitted 62 participants with a wearable eye tracker and instructed them to walk a route. Half of the participants were further instructed to avoid eye contact. We report that humans can flexibly allocate their gaze while navigating crowds and avoid eye contact primarily by orienting their head and eyes towards the floor. We discuss implications for crowd navigation and gaze behavior. In addition, we address a number of issues encountered in such field studies with regard to data quality, control of the environment, and participant adherence to instructions. We stress that methodological innovation and scientific progress are strongly interrelated.

Relationship between Cervicocephalic Kinesthetic Sensibility Measured during Dynamic Unpredictable Head Movements and Eye Movement Control or Postural Balance in Neck Pain Patients

Cervical afferent input is believed to affect postural balance and oculomotor control in neck pain patients, but its relationship to cervicocephalic kinesthesia, describing movement sense, has not yet been studied. The aim of this study was to analyze the relationship of two aspects of cervicocephalic kinesthesia to postural balance and oculomotor control in neck torsion positions. Forty-three idiopathic neck pain patients referred from orthopedic outpatient clinics and forty-two asymptomatic controls were enrolled in the study. A force plate was used to measure center-of-pressure movements during parallel stances under neutral and neck torsion maneuvers. Video-oculography was used to assess eye movements during smooth pursuit neck torsion test (SPNTT), while kinesthetic awareness was measured using the Butterfly test and head-to-neutral relocation test. Multiple regression was used to describe relationships between tests. Body sway in the anterior-posterior direction was related to Butterfly parameters but less to the head-to-neutral test. A medium relationship between Butterfly parameters and gain during SPNTT, with less SPNT-difference, was observed, but not for the head-to-neutral test. It can be concluded that specific aspect of neck kinesthetic functions (i.e., movement sense) importantly contributes towards oculomotor and balance control, which is more evident under neck torsion positions in neck pain patients, but is less pronounced in asymptomatic individuals.

Improvements of Warning Signs for Black Ice Based on Driving Simulator Experiments

Black ice is one of the main causes of traffic accidents in winter, and warning signs for black ice are generally ineffective because of the lack of credible information. To overcome this limitation, new warning signs for black ice were developed using materials that change color in response to different temperatures. The performance and effects of the new signs were investigated by conducting driver behavior analysis. To this end, driving simulator experiments were conducted with 37 participants for two different rural highway sections, i.e., a curve and a tangent. The analysis results of the driving behavior and visual behavior experiments showed that the conventional signs had insufficient performance in terms of inducing changes in driving behavior for safety. Meanwhile, the new signs actuated by weather conditions offered a statistically significant performance improvement. Typically, driver showed two times higher speed deceleration when they fixed eyes on the new weather-actuated warning sign (12.80 km/h) compared to the conventional old warning sign (6.84 km/h) in the curve segment. Accordingly, this study concluded that the new weather-actuated warning signs for black ice are more effective than the conventional ones for accident reduction during winters.

High-Accuracy 3D Gaze Estimation with Efficient Recalibration for Head-Mounted Gaze Tracking Systems

The problem of 3D gaze estimation can be viewed as inferring the visual axes from eye images. It remains a challenge especially for the head-mounted gaze tracker (HMGT) with a simple camera setup due to the complexity of the human visual system. Although the mainstream regression-based methods could establish the mapping relationship between eye image features and the gaze point to calculate the visual axes, it may lead to inadequate fitting performance and appreciable extrapolation errors. Moreover, regression-based methods suffer from a degraded user experience because of the increased burden in recalibration procedures when slippage occurs between HMGT and head. To address these issues, a high-accuracy 3D gaze estimation method along with an efficient recalibration approach is proposed with head pose tracking in this paper. The two key parameters, eyeball center and camera optical center, are estimated in head frame with geometry-based method, so that a mapping relationship between two direction features is proposed to calculate the direction of the visual axis. As the direction features are formulated with the accurately estimated parameters, the complexity of mapping relationship could be reduced and a better fitting performance can be achieved. To prevent the noticeable extrapolation errors, direction features with uniform angular intervals for fitting the mapping are retrieved over human’s field of view. Additionally, an efficient single-point recalibration method is proposed with an updated eyeball coordinate system, which reduces the burden of calibration procedures significantly. Our experiment results show that the calibration and recalibration methods could improve the gaze estimation accuracy by 35 percent (from a mean error of 2.00 degrees to 1.31 degrees) and 30 percent (from a mean error of 2.00 degrees to 1.41 degrees), respectively, compared with the state-of-the-art methods.

Oculomotor performance in patients with neck pain: Does it matter which angle of neck torsion is used in smooth pursuit eye movement test and is the agreement between angles dependent on target movement amplitude and velocity?

BACKGROUND

Neck torsion manoeuvre is thought to affect eye movement control via afferent sensory drive in neck pain disorders patients. Literature reports inconsistencies regarding the angle of neck torsion most commonly used across the studies.

OBJECTIVES

The goal of this study was to determine the level of agreement in oculomotor performance between two most commonly used neck torsion angles during smooth pursuit neck torsion test (SPNT).

DESIGN

A cross-sectional design was used in thirty-two neck pain patients and thirty-two healthy individuals.

METHOD

Gain and SPNT_diff were measured during SPNT test at 30° and 45° of neck torsion angle, at 30°, 40° and 50° of target movement amplitudes and three different target movement velocities (20°s^-1, 30°s^-1 and 40°s^-1) using eye tracking device. Bland-Altman plots and correlation analysis were used to study the agreement between the two angles.

RESULTS

Small to medium correlations and wide bias confidence intervals suggest medium level of agreement in gain or SPNT_diff between the two neck torsion angles for chronic neck pain patients, but higher in healthy individuals. Higher agreement in gain was observed at lager target movement amplitudes and at slower target movement velocities, however this trend was not observed for SPNT_diff.

CONCLUSION

Level of agreement between the two angles in SPNT test depends on the amplitude and velocity of the moving target. In cases when subjects within the same study are not able to perform 45° of neck torsion, 50° amplitude and 20°s^-1 velocity of target movement are more suitable to reach higher agreement between the angles.

Small head movements increase and colour noise in data from five video-based P-CR eye trackers

We empirically investigate the role of small, almost imperceptible balance and breathing movements of the head on the level and colour of noise in data from five commercial video-based P-CR eye trackers. By comparing noise from recordings with completely static artificial eyes to noise from recordings where the artificial eyes are worn by humans, we show that very small head movements increase levels and colouring of the noise in data recorded from all five eye trackers in this study. This increase of noise levels is seen not only in the gaze signal, but also in the P and CR signals of the eye trackers that provide these camera image features. The P and CR signals of the SMI eye trackers correlate strongly during small head movements, but less so or not at all when the head is completely still, indicating that head movements are registered by the P and CR images in the eye camera. By recording with artificial eyes, we can also show that the pupil size artefact has no major role in increasing and colouring noise. Our findings add to and replicate the observation by Niehorster et al., (2021) that lowpass filters in video-based P-CR eye trackers colour the data. Irrespective of source, filters or head movements, coloured noise can be confused for oculomotor drift. We also find that usage of the default head restriction in the EyeLink 1000+, the EyeLink II and the HiSpeed240 result in noisier data compared to less head restriction. Researchers investigating data quality in eye trackers should consider not using the Gen 2 artificial eye from SR Research / EyeLink. Data recorded with this artificial eye are much noisier than data recorded with other artificial eyes, on average 2.2-14.5 times worse for the five eye trackers.

Is Altered Oculomotor Control during Smooth Pursuit Neck Torsion Test Related to Subjective Visual Complaints in Patients with Neck Pain Disorders?

Subjective visual complaints are commonly reported in patients with neck pain, but their relation to objectively measured oculomotor functions during smooth pursuit neck torsion tests (SPNTs) has not yet been investigated. The aim of the study was to analyse classification accuracy of visual symptom intensity and frequency based on SPNT results. Forty-three patients with neck pain were referred by orthopaedic outpatient clinics where they were required to fill out 16-item proformas of visual complaints. Infrared video-oculography was used to measure smooth pursuit eye movements during neutral and neck torsion positions. Parameters of gain and SPNT difference (SPNT_diff) were taken into the Naïve Bayes model as classifiers, while intensity and frequency of visual symptoms were taken as predicted class. Intensity and, to a lesser degree, frequency of visual symptoms previously associated with neck pain or focal vision disorders (computer vision syndrome) showed better classification accuracy using gain at neck torsion position, indicating cervical driven visual disturbances. Moreover, SPNT_diff presented with slightly lower classification accuracy as compared to gain at neck torsion position. Our study confirmed the relationship between cervical driven oculomotor deficits and some visual complaints (concentrating to read, words moving on page, blurred vision, difficulty judging distance, sore eyes, heavy eyes, red eyes, and eyes strain).

Beyond screen time: Using head-mounted eye tracking to study natural behavior

Head-mounted eye tracking is a new method that allows researchers to catch a glimpse of what infants and children see during naturalistic activities. In this chapter, we review how mobile, wearable eye trackers improve the construct validity of important developmental constructs, such as visual object experiences and social attention, in ways that would be impossible using screen-based eye tracking. Head-mounted eye tracking improves ecological validity by allowing researchers to present more realistic and complex visual scenes, create more interactive experimental situations, and examine how the body influences what infants and children see. As with any new method, there are difficulties to overcome. Accordingly, we identify what aspects of head-mounted eye-tracking study design affect the measurement quality, interpretability of the results, and efficiency of gathering data. Moreover, we provide a summary of best practices aimed at allowing researchers to make well-informed decisions about whether and how to apply head-mounted eye tracking to their own research questions.

How to choose the size of facial areas of interest in interactive eye tracking

Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer's test conditions, validation is essential with regard to the quality of gaze data and other factors potentially threatening the validity of this signal. In this study, we evaluated the impact of accuracy and areas of interest (AOIs) size on the classification of simulated gaze (fixation) data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying accuracy. As hypothesized, we found that accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed in falsely classified gaze inside AOIs (Type I errors; false alarms) and falsely classified gaze outside the predefined AOIs (Type II errors; misses). Our results indicate that smaller AOIs generally minimize false classifications as long as accuracy is good enough. For studies with lower accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of more probable Type I errors. Proper estimation of accuracy is therefore essential for making informed decisions regarding the size of AOIs in eye tracking research.

The influence of neck torsion and sequence of cycles on intra-trial reliability of smooth pursuit eye movement test in patients with neck pain disorders

The sensory mismatch commonly observed in patients with neck pain disorders could alter intra-trial reliability in simple implicit smooth pursuit eye movement tasks. This could be more pronounced when neck is in torsioned position (SPNT). The aim of this study was to explore the effects of neck torsion, target movement velocity and amplitude on intra-trial reliability of smooth pursuit eye movements in patients with neck pain disorders and healthy individuals. SPNT test was evaluated in 32 chronic neck pain patients and 32 healthy controls. Ten cycles were performed using video-oculography at three different velocities (20° s^-1, 30° s^-1 and 40° s^-1) and at three different amplitudes (30°, 40° and 50°) of target movement. Intra-trial reliability and differences between average gain and SPNT difference from the second to fifth cycle and from the sixth to ninth cycle were assessed using ICC_3.1 and factorial analysis of variance, respectively. Intra-trial reliability for gain and SPNT difference at all target movement amplitudes and velocities proved to be good to excellent in both observed groups. Patients with neck pain disorders presented with a trend of inferior gain performance between the sixth and ninth cycle at 30° s^-1 of target movement as compared to healthy individuals which was only evident when neck was in torsioned position. Although intra-trial reliability of smooth pursuit neck torsion test is good to excellent, the effects of learning are not as pronounced in patients with neck pain disorders.

Detecting Soldiers' Fatigue Using Eye-Tracking Glasses: Practical Field Applications and Research Opportunities

INTRODUCTION

Objectively determining soldiers' fatigue levels could help prevent injuries or accidents resulting from inattention or decreased alertness. Eye-tracking technologies, such as optical eye tracking (OET) and electrooculography (EOG), are often used to monitor fatigue. Eyeblinks-especially blink frequency and blink duration-are known as easily observable and valid biomarkers of fatigue. Currently, various eye trackers (i.e., eye-tracking glasses) are available on the market using either OET or EOG technologies. These wearable eye trackers offer several advantages, including unobtrusive functionality, practicality, and low costs. However, several challenges and limitations must be considered when implementing these technologies in the field to monitor fatigue levels. This review investigates the feasibility of eye tracking in the field focusing on the practical applications in military operational environments.

MATERIALS AND METHOD

This paper summarizes the existing literature about eyeblink dynamics and available wearable eye-tracking technologies, exposing challenges and limitations, as well as discussing practical recommendations on how to improve the feasibility of eye tracking in the field.

RESULTS

So far, no eye-tracking glasses can be recommended for use in a demanding work environment. First, eyeblink dynamics are influenced by multiple factors; therefore, environments, situations, and individual behavior must be taken into account. Second, the glasses' placement, sunlight, facial or body movements, vibrations, and sweat can drastically decrease measurement accuracy. The placement of the eye cameras for the OET and the placement of the electrodes for the EOG must be chosen consciously, the sampling rate must be minimal 200 Hz, and software and hardware must be robust to resist any factors influencing eye tracking.

CONCLUSION

Monitoring physiological and psychological readiness of soldiers, as well as other civil professionals that face higher risks when their attention is impaired or reduced, is necessary. However, improvements to eye-tracking devices' hardware, calibration method, sampling rate, and algorithm are needed in order to accurately monitor fatigue levels in the field.

Gaze and speech behavior in parent–child interactions: The role of conflict and cooperation

A primary mode of human social behavior is face-to-face interaction. In this study, we investigated the characteristics of gaze and its relation to speech behavior during video-mediated face-to-face interactions between parents and their preadolescent children. 81 parent–child dyads engaged in conversations about cooperative and conflictive family topics. We used a dual-eye tracking setup that is capable of concurrently recording eye movements, frontal video, and audio from two conversational partners. Our results show that children spoke more in the cooperation-scenario whereas parents spoke more in the conflict-scenario. Parents gazed slightly more at the eyes of their children in the conflict-scenario compared to the cooperation-scenario. Both parents and children looked more at the other's mouth region while listening compared to while speaking. Results are discussed in terms of the role that parents and children take during cooperative and conflictive interactions and how gaze behavior may support and coordinate such interactions.

The application of noninvasive, restraint-free eye-tracking methods for use with nonhuman primates

Over the past 50 years there has been a strong interest in applying eye-tracking techniques to study a myriad of questions related to human and nonhuman primate psychological processes. Eye movements and fixations can provide qualitative and quantitative insights into cognitive processes of nonverbal populations such as nonhuman primates, clarifying the evolutionary, physiological, and representational underpinnings of human cognition. While early attempts at nonhuman primate eye tracking were relatively crude, later, more sophisticated and sensitive techniques required invasive protocols and the use of restraint. In the past decade, technology has advanced to a point where noninvasive eye-tracking techniques, developed for use with human participants, can be applied for use with nonhuman primates in a restraint-free manner. Here we review the corpus of recent studies (N=32) that take such an approach. Despite the growing interest in eye-tracking research, there is still little consensus on "best practices," both in terms of deploying test protocols or reporting methods and results. Therefore, we look to advances made in the field of developmental psychology, as well as our own collective experiences using eye trackers with nonhuman primates, to highlight key elements that researchers should consider when designing noninvasive restraint-free eye-tracking research protocols for use with nonhuman primates. Beyond promoting best practices for research protocols, we also outline an ideal approach for reporting such research and highlight future directions for the field.

Object-Gaze Distance: Quantifying Near- Peripheral Gaze Behavior in Real-World Applications

Eye tracking (ET) has shown to reveal the wearer’s cognitive processes using the measurement of the central point of foveal vision. However, traditional ET evaluation methods have not been able to take into account the wearers’ use of the peripheral field of vision. We propose an algorithmic enhancement to a state-of-the-art ET analysis method, the Object- Gaze Distance (OGD), which additionally allows the quantification of near-peripheral gaze behavior in complex real-world environments. The algorithm uses machine learning for area of interest (AOI) detection and computes the minimal 2D Euclidean pixel distance to the gaze point, creating a continuous gaze-based time-series. Based on an evaluation of two AOIs in a real surgical procedure, the results show that a considerable increase of interpretable fixation data from 23.8 % to 78.3 % of AOI screw and from 4.5 % to 67.2 % of AOI screwdriver was achieved, when incorporating the near-peripheral field of vision. Additionally, the evaluation of a multi-OGD time series representation has shown the potential to reveal novel gaze patterns, which may provide a more accurate depiction of human gaze behavior in multi-object environments.

Post-processing integration and semi-automated analysis of eye-tracking and motion-capture data obtained in immersive virtual reality environments to measure visuomotor integration

Mobile eye-tracking and motion-capture techniques yield rich, precisely quantifiable data that can inform our understanding of the relationship between visual and motor processes during task performance. However, these systems are rarely used in combination, in part because of the significant time and human resources required for post-processing and analysis. Recent advances in computer vision have opened the door for more efficient processing and analysis solutions. We developed a post-processing pipeline to integrate mobile eye-tracking and full-body motion-capture data. These systems were used simultaneously to measure visuomotor integration in an immersive virtual environment. Our approach enables calculation of a 3D gaze vector that can be mapped to the participant's body position and objects in the virtual environment using a uniform coordinate system. This approach is generalizable to other configurations, and enables more efficient analysis of eye, head, and body movements together during visuomotor tasks administered in controlled, repeatable environments.

Eye-tracking glasses in face-to-face interactions: Manual versus automated assessment of areas-of-interest

The assessment of gaze behaviour is essential for understanding the psychology of communication. Mobile eye-tracking glasses are useful to measure gaze behaviour during dynamic interactions. Eye-tracking data can be analysed by using manually annotated areas-of-interest. Computer vision algorithms may alternatively be used to reduce the amount of manual effort, but also the subjectivity and complexity of these analyses. Using additional re-identification (Re-ID) algorithms, different participants in the interaction can be distinguished. The aim of this study was to compare the results of manual annotation of mobile eye-tracking data with the results of a computer vision algorithm. We selected the first minute of seven randomly selected eye-tracking videos of consultations between physicians and patients in a Dutch Internal Medicine out-patient clinic. Three human annotators and a computer vision algorithm annotated mobile eye-tracking data, after which interrater reliability was assessed between the areas-of-interest annotated by the annotators and the computer vision algorithm. Additionally, we explored interrater reliability when using lengthy videos and different area-of-interest shapes. In total, we analysed more than 65 min of eye-tracking videos manually and with the algorithm. Overall, the absolute normalized difference between the manual and the algorithm annotations of face-gaze was less than 2%. Our results show high interrater agreements between human annotators and the algorithm with Cohen’s kappa ranging from 0.85 to 0.98. We conclude that computer vision algorithms produce comparable results to those of human annotators. Analyses by the algorithm are not subject to annotator fatigue or subjectivity and can therefore advance eye-tracking analyses.

Eyeblink Detection in the Field: A Proof of Concept Study of Two Mobile Optical Eye-Trackers

Introduction

High physical and cognitive strain, high pressure, and sleep deficit are part of daily life for military professionals and civilians working in physiologically demanding environments. As a result, cognitive and physical capacities decline and the risk of illness, injury, or accidents increases. Such unfortunate outcomes could be prevented by tracking real-time physiological information, revealing individuals’ objective fatigue levels. Oculometrics, and especially eyeblinks, have been shown to be promising biomarkers that reflect fatigue development. Head-mounted optical eye-trackers are a common method to monitor these oculometrics. However, studies measuring eyeblink detection in real-life settings have been lacking in the literature. Therefore, this study aims to validate two current mobile optical eye-trackers in an unrestrained military training environment.

Materials and Method

Three male participants (age 20.0 ± 1.0) of the Swiss Armed Forces participated in this study by wearing three optical eye-trackers, two VPS16s (Viewpointsystem GmbH, Vienna, Austria) and one Pupil Core (Pupil Labs GmbH, Berlin, Germany), during four military training events: Healthcare education, orienteering, shooting, and military marching. Software outputs were analyzed against a visual inspection (VI) of the video recordings of participants’ eyes via the respective software. Absolute and relative blink numbers were provided. Each blink detected by the software was classified as a “true blink” (TB) when it occurred in the software output and the VI at the same time, as a “false blink” (FB) when it occurred in the software but not in the VI, and as a “missed blink” (MB) when the software failed to detect a blink that occurred in the VI. The FBs were further examined for causes of the incorrect recordings, and they were divided into four categories: “sunlight,” “movements,” “lost pupil,” and “double-counted”. Blink frequency (i.e., blinks per minute) was also analyzed.

Results

Overall, 49.3% and 72.5% of registered eyeblinks were classified as TBs for the VPS16 and Pupil Core, respectively. The VPS16 recorded 50.7% of FBs and accounted for 8.5% of MBs, while the Pupil Core recorded 27.5% of FBs and accounted for 55.5% of MBs. The majority of FBs—45.5% and 73.9% for the VPS16 and Pupil Core, respectively—were erroneously recorded due to participants’ eye movements while looking up, down, or to one side. For blink frequency analysis, systematic biases (±limits of agreement) stood at 23.3 (±43.5) and −4.87 (±14.1) blinks per minute for the VPS16 and Pupil Core, respectively. Significant differences in systematic bias between devices and the respective VIs were found for nearly all activities (P < .05).

Conclusion

An objective physiological monitoring of fatigue is necessary for soldiers as well as civil professionals who are exposed to higher risks when their cognitive or physical capacities weaken. However, optical eye-trackers’ accuracy has not been specified under field conditions—especially not in monitoring fatigue. The significant overestimation and underestimation of the VPS16 and Pupil Core, respectively, demonstrate the general difficulty of blink detection in the field.

Eye-Tracking for Clinical Ophthalmology with Virtual Reality (VR): A Case Study of the HTC Vive Pro Eye's Usability

BACKGROUND

A case study is proposed to empirically test and discuss the eye-tracking status-quo hardware capabilities and limitations of an off-the-shelf virtual reality (VR) headset with embedded eye-tracking for at-home ready-to-go online usability in ophthalmology applications.

METHODS

The eye-tracking status-quo data quality of the HTC Vive Pro Eye is investigated with novel testing specific to objective online VR perimetry. Testing was done across a wide visual field of the head-mounted-display's (HMD) screen and in two different moving conditions. A new automatic and low-cost Raspberry Pi system is introduced for VR temporal precision testing for assessing the usability of the HTC Vive Pro Eye as an online assistance tool for visual loss.

RESULTS

The target position on the screen and head movement evidenced limitations of the eye-tracker capabilities as a perimetry assessment tool. Temporal precision testing showed the system's latency of 58.1 milliseconds (ms), evidencing its good potential usage as a ready-to-go online assistance tool for visual loss.

CONCLUSIONS

The test of the eye-tracking data quality provides novel analysis useful for testing upcoming VR headsets with embedded eye-tracking and opens discussion regarding expanding future introduction of these HMDs into patients' homes for low-vision clinical usability.

Characterizing gaze position signals and synthesizing noise during fixations in eye-tracking data

The magnitude of variation in the gaze position signals recorded by an eye tracker, also known as its precision, is an important aspect of an eye tracker’s data quality. However, data quality of eye-tracking signals is still poorly understood. In this paper, we therefore investigate the following: (1) How do the various available measures characterizing eye-tracking data during fixation relate to each other? (2) How are they influenced by signal type? (3) What type of noise should be used to augment eye-tracking data when evaluating eye-movement analysis methods? To support our analysis, this paper presents new measures to characterize signal type and signal magnitude based on RMS-S2S and STD, two established measures of precision. Simulations are performed to investigate how each of these measures depends on the number of gaze position samples over which they are calculated, and to reveal how RMS-S2S and STD relate to each other and to measures characterizing the temporal spectrum composition of the recorded gaze position signal. Further empirical investigations were performed using gaze position data recorded with five eye trackers from human and artificial eyes. We found that although the examined eye trackers produce gaze position signals with different characteristics, the relations between precision measures derived from simulations are borne out by the data. We furthermore conclude that data with a range of signal type values should be used to assess the robustness of eye-movement analysis methods. We present a method for generating artificial eye-tracker noise of any signal type and magnitude.

Examining the effect of online advertisement cues on human responses using eye-tracking, EEG, and MRI

This study sought to emphasize how disciplines such as neuroscience and marketing can be applied in advertising and consumer behavior. The application of neuroscience methods in analyzing and understanding human behavior related to the Elaboration Likelihood Model (ELM) and brain activity has recently garnered attention. This study examines brain processes while participants attempted to elicit preferences for a product, and demonstrates factors that influence consumer behavior using eye-tracking, electroencephalography (EEG), and magnetic resonance imaging (MRI) from a neuroscience approach. We planned two conditions of online advertising, namely, peripheral cues without argument and central cues with argument strength. Thirty respondents participated in the experiment, consisting of eye-tracking, EEG, and MRI instruments to explore brain activity in central cue conditions. We investigated whether diffusion tensor imaging (DTI) analysis could detect regional brain changes. Using eye-tracking, we found that the responses were mainly in the mean fixation duration, number of fixations, mean saccade duration, and number of saccade durations for the central cue condition. Moreover, the findings show that the fusiform gyrus and frontal cortex are significantly associated with building a relationship by inferring central cues in the EEG assay. The MRI images show that the fusiform gyrus and frontal cortex are significantly active in the central cue condition. DTI analysis indicates that the corpus callosum has changed in the central cue condition. We used eye-tracking, EEG, MRI, and DTI to understand that these connections may apprehend responses when viewing advertisements, especially in the fusiform gyrus, frontal cortex, and corpus callosum.

Eye tracking in human interaction: Possibilities and limitations

There is a long history of interest in looking behavior during human interaction. With the advance of (wearable) video-based eye trackers, it has become possible to measure gaze during many different interactions. We outline the different types of eye-tracking setups that currently exist to investigate gaze during interaction. The setups differ mainly with regard to the nature of the eye-tracking signal (head- or world-centered) and the freedom of movement allowed for the participants. These features place constraints on the research questions that can be answered about human interaction. We end with a decision tree to help researchers judge the appropriateness of specific setups.