Eye-tracking Equipment Research Articles

Service experience lies in the eye of the beholder: contextualizing extant literature toward integrating eye-tracking in service research

Purpose In spite of offering clear benefits and increased availability, relatively few service research studies rely on eye-tracking. Therefore, this paper aims to assist service researchers in harnessing the vast capabilities of eye-tracking technologies and methods for their own inquiries. Design/methodology/approach In addition to systematically reviewing extant research in the service domain and the wider marketing field with respect to the fundamentals and practices of eye-tracking, this paper presents a concise, empirical eye-tracking demonstration. These contributions suggest future outlooks for how to incorporate eye-tracking more effectively in service research. Findings The systematic literature review informs a comprehensive framework for integrating eye-tracking in service research that comprises research question focus regarding higher-order psychological constructs of interest, appropriate study settings, sample composition, optimal eye-tracking equipment and operationalization considerations. Research limitations/implications By establishing a common ground and recommended uses of eye-tracking for service research, this study equips service scholars with the knowledge they need regarding eye-tracking fundamentals, common practices and future outlooks. A simple, empirical example further demonstrates some options for unlocking the unique capabilities of eye-tracking in service research and uncovering the complexities inherent to service experiences and other core service concepts. Originality/value This paper compiles and contextualizes insights from existing eye-tracking research, which it uses to draw important lessons for deploying eye-tracking in service domains.

Scanpath Prediction on Information Visualisations.

We propose Unified Model of Saliency and Scanpaths (UMSS)- a model that learns to predict multi-duration saliency and scanpaths (i.e. sequences of eye fixations) on information visualisations. Although scanpaths provide rich information about the importance of different visualisation elements during the visual exploration process, prior work has been limited to predicting aggregated attention statistics, such as visual saliency. We present in-depth analyses of gaze behaviour for different information visualisation elements (e.g. Title, Label, Data) on the popular MASSVIS dataset. We show that while, overall, gaze patterns are surprisingly consistent across visualisations and viewers, there are also structural differences in gaze dynamics for different elements. Informed by our analyses, UMSS first predicts multi-duration element-level saliency maps, then probabilistically samples scanpaths from them. Extensive experiments on MASSVIS show that our method consistently outperforms state-of-the-art methods with respect to several, widely used scanpath and saliency evaluation metrics. Our method achieves a relative improvement in sequence score of 11.5% for scanpath prediction, and a relative improvement in Pearson correlation coefficient of up to 23.6% for saliency prediction. These results are auspicious and point towards richer user models and simulations of visual attention on visualisations without the need for any eye tracking equipment.

The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review.

Machine learning (ML) has revolutionized medical image-based diagnostics. In this review, we cover a rapidly emerging field that can be potentially significantly impacted by ML - eye tracking in medical imaging. The review investigates the clinical, algorithmic, and hardware properties of the existing studies. In particular, it evaluates 1) the type of eye-tracking equipment used and how the equipment aligns with study aims; 2) the software required to record and process eye-tracking data, which often requires user interface development, and controller command and voice recording; 3) the ML methodology utilized depending on the anatomy of interest, gaze data representation, and target clinical application. The review concludes with a summary of recommendations for future studies, and confirms that the inclusion of gaze data broadens the ML applicability in Radiology from computer-aided diagnosis (CAD) to gaze-based image annotation, physicians' error detection, fatigue recognition, and other areas of potentially high research and clinical impact.

Insights into Rett Syndrome girls' receptive vocabulary through eye movements and parental perception

ObjectiveThis study evaluated the receptive vocabulary of girls diagnosed with Rett Syndrome (RS) by employing eye-tracking technology and examined how these objective measures compared with parents' perceptions of their daughters' language abilities. MethodFourteen girls with RS and eleven typically developing peers participated. Instruments included the Kerr Scale, a parental questionnaire on communication skills, the Peabody Picture Vocabulary Test - PPVT-4, and eye-tracking equipment. The PPVT-4's initial 12 cards, each displaying four images, were presented on screen for 5 s for the child's initial inspection. Subsequently, the same card was shown for 5 s with instructions to identify the picture matching the word, repeated three times in a randomized order. ResultsEye-tracking assessments revealed that girls with RS with less severe symptoms, performed below typically developing peers with aged 3–4 years. The number of eye fixations emerged as a reliable metric for assessing their performance. A positive correlation was found between parental reports of their daughters' vocabulary knowledge and their ability to identify the correct stimulus, suggesting comprehension and active engagement in the testing process. ConclusionThis study presents a pioneering approach by combining parental perceptions with eye-tracking measures to assess receptive vocabulary in girls diagnosed with Rett Syndrome. Despite showing lower performance levels compared to significantly younger peers, the findings suggest that these individuals use less effectively eye contact as a mode of communication.

When time drives search effort: the effect of assortment variety on visual attention to SKU pricing

PurposeUnderstanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.Design/methodology/approachTwo experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.FindingsThe results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.Practical implicationsMarketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.Originality/valueOur findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

How Scientists Use Webcams to Track Human Gaze

Eye tracking is a technology that can record people’s eye movements and tell scientists what people look at on screens or out in the world. Scientists use eye tracking to understand what people notice or remember; marketing researchers who create ads use eye tracking to see what type of ads or products capture people’s attention; and video game designers use eye tracking to see what parts of a game are confusing to players, so designers can fix the game. Eye-tracking equipment can be expensive and time consuming for researchers to use, so is there another way to record eye movements without buying an eye tracker? There is! Computer scientists can use a computer-based method called machine learning to turn an everyday webcam into an eye tracker. They can even do this with mobile phones! In this article, you will learn about how eye trackers work and the advantages of disadvantages of using webcams to track eyes.

Effect of Target Differentiation, Prioritization, and Environmental Clutter on Quiet Eye Duration in First-Person Shooter Esports: A Brief Report Pilot Study

The burgeoning prominence of esports underscores its increasing relevance in sport and performance psychology. To enhance its integration into scholarly discourse, established cognitive research paradigms should be applied. In this study, we focused on first-person shooter esports, identifying specific variables unique to this domain and examining their impact on quiet eye (QE) duration—an indicator strongly correlated with successful performance. Using eye-tracking equipment, we analyzed gaze data related to the QE, the final fixation point preceding a motor response. Our pilot sample (n = 9) participated in three block trials exploring the effects of environmental clutter, target differentiation, and target prioritization on QE duration. Paired t tests compared mean QE duration between experimental tasks and control trials with single targets. Although trend effects of environmental clutter and target prioritization were observed, none reached statistical significance. These findings echo certain aspects of the existing esports literature, particularly regarding the reduced prominence of QE in scenarios involving multiple targets. Acknowledging study limitations, we offer recommendations for future research to deepen understanding of cognitive processes and performance outcomes in esports.

Computer-based assessment in mathematics

Computer-based assessments is becoming more and more common in mathematics education, and because the digital media entails other demands than paper-based tests, potential threats against validity must be considered. In this study we investigate how preparatory instructions and digital familiarity, may be of importance for test validity. 77 lower secondary students participated in the study and were divided into two groups that received different instructions about five different types of dynamic and/or interactive functions in digital mathematics items. One group received a verbal and visual instruction, whereas the other group also got the opportunity to try using the functions themselves. The students were monitored using eye-tracking equipment during their work with mathematics items with the five types of functions. The result revealed differences in how the students undertook the dynamic functions due to the students’ preparatory instructions. One conclusion is that students need to be very familiar with dynamic and interactive functions in tests, if validity is to be ensured. The validity also depends on the type of dynamic function used.

Usability of Marine Geographic Information System Software for User Area of Interest Analysis Using Eye-Tracking Equipment

Usability of Marine Geographic Information System Software for User Area of Interest Analysis Using Eye-Tracking Equipment

Assessing the effects of road geometry and fidelity on driver behaviour in driving simulator experiments

The paper presents a set of programs created specifically to investigate the driver’s behaviour along a road circuit when the driving simulation scenario changes in the quantity and quality of the displayed Level of Details (LOD) (fidelity), as well as when the road curvature ratio (geometry) varies. In the experiments, carried out on a sample of 29 drivers who drove on the same circuit twice, data on vehicle features (speed, trajectory, and gas pedal usage), physiological factors of the drivers (SC, skin conductance), and information from an eye-tracking equipment (gaze) were collected. The programs used in this study are designed to study the complex and position-based information present in the data that cannot be analysed by classical statistical methods. The results are twofold. On one side, they show the applicability and usefulness of the proposed functions, which are capable of extracting information and referring it to a specific point in the circuit. On the other side, they give effective insights on driving behaviour. When driving is more demanding (i.e., along curvilinear stretches), variations between different scenarios are nearly non-existent, and the effect of geometry changes greatly depending on the signal being investigated (speed, trajectory, gas pedal, gaze, skin conductance). The effects of vehicle speed are essentially the same for all drivers and are closely tied to the geometry of the road. Trajectory and gas-pedal usage signals exhibit diverse effects on drivers, indicating that their choice of trajectory and frequency of gas-pedal usage is undoubtedly influenced by their driving style as well as by geometry. Skin conductance appears to be significantly altered where driving is more challenging, but it varies greatly from driver to driver. The results of gaze analysis also demonstrate that the driver’s behaviour strongly depends on geometry and much less on LOD and loop sequence.

A tool for measuring mental workload during prosthesis use: The Prosthesis Task Load Index (PROS-TLX).

When using a upper-limb prosthesis, mental, emotional, and physical effort is often experienced. These have been linked to high rates of device dissatisfaction and rejection. Therefore, understanding and quantifying the complex nature of workload experienced when using, or learning to use, a upper-limb prosthesis has practical and clinical importance for researchers and applied professionals. The aim of this paper was to design and validate a self-report measure of mental workload specific to prosthesis use (The Prosthesis Task Load Index; PROS-TLX) that encapsulates the array of mental, physical, and emotional demands often experienced by users of these devices. We first surveyed upper-limb prosthetic limb users who confirmed the importance of eight workload constructs taken from published literature and previous workload measures. These constructs were mental demands, physical demands, visual demands, conscious processing, frustration, situational stress, time pressure and device uncertainty. To validate the importance of these constructs during initial prosthesis learning, we then asked able-bodied participants to complete a coin-placement task using their anatomical hand and then using a myoelectric prosthesis simulator under low and high mental workload. As expected, using a prosthetic hand resulted in slower movements, more errors, and a greater tendency to visually fixate the hand (indexed using eye-tracking equipment). These changes in performance were accompanied by significant increases in PROS-TLX workload subscales. The scale was also found to have good convergent and divergent validity. Further work is required to validate whether the PROS-TLX can provide meaningful clinical insights to the workload experienced by clinical users of prosthetic devices.

웨어러블向 시선추적 기법에 관한 연구

The eye tracking technology is widespread all around the society, and is demonstrating great performances in both preciseness and convenience. Hereby we can glimpse new possibility of an interface’s conduct without screen-touching. This technology can become a new way of conversation for those including but not limited to the patients suffering from Lou Gehrig’s disease, who are paralyzed each part by part of the body and finally cannot help but only moving eyes. Formerly in that case, the patients were given nothing to do but waiting for the death, even being unable to communicate with there families. A new interface that harnesses eyes as a new means of communication, although it conveys great difficulty, can be helpful for them. There surely are some eye tracking systems and equipment for their exclusive uses on the market. Notwithstanding, several obstacles including the complexity of operation and their high prices of over 12 million won($9,300) are hindering universal supply to people and coverage for the patients. Therefore, this paper suggests wearable-type eye tracking device that can support minorities and vulnerable people and be occupied inexpensively and study eye tracking method in order to maximize the possibility of future development across the world, finally proposing the way of designing and developing a brought-down costed eye tracking system based on high-efficient wearable device.

Usability Evaluation with Eye Tracking: The Case of a Mobile Augmented Reality Application with Historical Images for Urban Cultural Heritage

Eye-tracking technologies have matured significantly in recent years and have become more affordable and easier to use. We investigated how eye-tracking technology can be applied to evaluate the usability of mobile augmented reality applications with historical images for urban cultural heritage. The experiment involved a series of complex user evaluation sessions, combining semi-structured interviews, observations, think-aloud protocol, SUS questionnaire, and product reaction cards, complemented by eye tracking, to gather insights on the Spotlight Timisoara AR mobile application, part of a digital storytelling multiplatform for the city of Timisoara (Romania), soon to be European Capital of Culture in 2023. The results indicate strong and weak aspects of the application, both as expressed by the participants and as derived from analyzing the eye-tracking data. The paper also lists the main challenges we identified in using eye-tracking equipment to evaluate the usability of such mobile augmented reality applications for urban outdoor heritage.

Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology.

Lack of visual recognition of colorectal polyps may lead to interval cancers. The mechanisms contributing to perceptual variation, particularly for subtle and advanced colorectal neoplasia, have scarcely been investigated. We aimed to evaluate visual recognition errors and provide novel mechanistic insights. Eleven participants (seven trainees and four medical students) evaluated images from the UCL polyp perception dataset, containing 25 polyps, using eye-tracking equipment. Gaze errors were defined as those where the lesion was not observed according to eye-tracking technology. Cognitive errors occurred when lesions were observed but not recognized as polyps by participants. A video study was also performed including 39 subtle polyps, where polyp recognition performance was compared with a convolutional neural network. Cognitive errors occurred more frequently than gaze errors overall (65.6%), with a significantly higher proportion in trainees (P=0.0264). In the video validation, the convolutional neural network detected significantly more polyps than trainees and medical students, with per-polyp sensitivities of 79.5%, 30.0%, and 15.4%, respectively. Cognitive errors were the most common reason for visual recognition errors. The impact of interventions such as artificial intelligence, particularly on different types of perceptual errors, needs further investigation including potential effects on learning curves. To facilitate future research, a publicly accessible visual perception colonoscopy polyp database was created.

Ophthalmic Manifestations, Evaluation, and Guidelines for Testing of Concussion

Early detection and treatment of concussions is crucial to preventing further brain damage. Current subjective standard-of-care tests used to diagnose concussions, such as symptom reporting and standardized concussion checklists, can often underdiagnose patients with concussions. This review will cover novel biomarkers of concussions related to concussion-associated visual deficits and how they can be used to more accurately monitor patient concussion symptom improvement. Visual deficits are seen in up to 90% of patients within hours after a concussion-inducing trauma and can serve as objective biomarkers in diagnosing and monitoring concussions. Some of the key visual deficits that are seen in patients with concussions include convergence insufficiency, problems with accommodation and smooth pursuit eye movements, saccade dysfunction, and decreased optokinetic nystagmus gain. Patients frequently report blurred vision, challenges reading, double vision and eyestrain, dizziness, visual field defects, and light sensitivity, related to concussions. Promising eye tests to detect and track concussions include pupillary light reflexes, the circle test, and the Samandarani group’s non-spatially calibrated binocular motility test/algorithm in conjunction with video oculography and eye tracking equipment. The EYE-SYNC eye-tracking device allows for portable and accurate detection of eye movements in the field and is a promising tool for detecting concussions both in the field and clinic. Optical coherence tomography and other retinal imaging modalities also represent a promising method of identifying individuals who have sustained a concussion.

A real 3D scene rendering optimization method based on region of interest and viewing frustum prediction in virtual reality

ABSTRACT As an important technology of digital construction, real 3D models can improve the immersion and realism of virtual reality (VR) scenes. The large amount of data for real 3D scenes requires more effective rendering methods, but the current rendering optimization methods have some defects and cannot render real 3D scenes in virtual reality. In this study, the location of the viewing frustum is predicted by a Kalman filter, and eye-tracking equipment is used to recognize the region of interest (ROI) in the scene. Finally, the real 3D model of interest in the predicted frustum is rendered first. The experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance, the prediction accuracy is approximately 87%, the scene rendering efficiency is improved by 8.3%, and the motion sickness is reduced by approximately 54.5%. These studies help promote the use of real 3D models in virtual reality and ROI recognition methods. In future work, we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes.

The Application of Eye-Tracking Technology in the Assessment of Radiology Practices: A Systematic Review

The aim of this review is to provide an in-depth analysis of literature pertaining to the use of eye-tracking equipment in the evaluation of radiological image interpretation by professionals in clinical practice. A systematic search of current literature was conducted through the databases of CINAHL, Medline, ProQuest, PubMed, Scopus, Web of Science and Wiley Online Library. A total of 25 articles were included in the final analysis. The literature gathered referenced four main discussions, which were competency assessment, educational tools, visual search behaviour and assistive aid evaluations. The majority of articles (68%) referenced to the competency assessment of professional groups yet appeared to have conflicting results within the categories of speed and eye-metrics. Significant conclusions could be made pertaining to confidence (100%) and accuracy measurements (56%), which suggested a background of higher experience correlates to a higher rate of accuracy and a higher confidence level. Other findings regarding the main themes focused on eye-tracking as an educational tool, where the literature suggests that such equipment may be useful in improving educational repertoire and interpretation technique. Literature pertaining to the visual search behaviour analysis and the evaluation of assistive aids did not provide strong conclusions due to research limitations. Whilst the use of eye-tracking in the analysis of radiological practices is a promising new venture to quantify the interpretation patterns of professionals, undertaking future research is recommended to solidify conclusions and provide greater insight.

Tunnel safety: A pilot study investigating drivers’ fixation characteristics when approaching tunnel entrance at different driving speeds

This study presents the results of a driving experiment study on spatiotemporal characteristics of drivers’ fixation when entering a tunnel portal with different driving speeds. The study was performed during the daytime in a relatively long tunnel. Six experienced drivers were recruited to participate in the driving experiment. Experimental data of pupil area and fixation point position (from 200 m before the tunnel to the tunnel portal) were collected by non-intrusive eye-tracking equipment for three predetermined vehicle speeds (40 km/h, 60 km/h and 80 km/h). Fixation maps (color-coded maps showing distributed data) were created from fixation point position data to quantify visual behaviour changes. The results demonstrated that vehicle speed has a significant impact on pupil area and fixation zones. Fixation area and average pupil area had a significant negative correlation with vehicle speed during the daytime. Moreover, drivers concentrated more on the tunnel entrance portal, front road pavement and car control wheeling. The results revealed that the relationship between pupil area and vehicle speed fitted an exponential function. Limitations and future directions of the study are also discussed.

Impacts of Cues on Learning and Attention in Immersive 360-Degree Video: An Eye-Tracking Study.

Immersive 360-degree video has become a new learning resource because of its immersive sensory experience. This study examined the effects of textual and visual cues on learning and attention in immersive 360-degree video by using eye-tracking equipment integrated in a virtual reality head-mounted display. Participants (n = 110) were randomly assigned to one of four conditions: (1) no cues, (2) textual cues in the initial field of view (FOV), (3) textual cues outside the initial FOV, and (4) textual cues outside the initial FOV + visual cues. The results showed that the cues (annotations or annotations + arrows) helped learners achieve better learning outcomes and spend more time focusing on the areas with cues. In addition, the study found a serious imbalance in the distribution of learners’ attention in each region of the video. The attention directed to textual cues in the initial FOV is much higher than the attention directed to textual cues outside the initial FOV. Adding visual cues can effectively direct attention to textual cues outside the initial FOV and alleviate the imbalance of attention distribution. Consequently, adding cues to immersive 360-degree video can be an appropriate approach to promote learning and guide attention in immersive 360-degree video learning environments. This study provided new insights into the design and development of immersive 360-degree video instructional resources.

Object Selection as a Biometric.

The use of eye movement as a biometric is a new biometric technology that is now in competition with many other technologies such as the fingerprint, face recognition, ear recognition and many others. Problems encountered with these authentication methods such as passwords and tokens have led to the emergence of biometric authentication techniques. Biometric authentication involves the use of physical or behavioral characteristics to identify people. In biometric authentication, feature extraction is a very vital stage, although some of the extracted features that are not very useful may lead to the degradation of the biometric system performance. Object selection using eye movement as a technique for biometric authentication was proposed for this study. To achieve this, an experiment for collecting eye movement data for biometric purposes was conducted. Eye movement data were measured from twenty participants during choosing and finding of still objects. The eye-tracking equipment used was able to measure eye-movement data. The model proposed in this paper aimed to create a template from these observations that tried to assign a unique binary signature for each enrolled user. Error correction is used in authenticating a user who submits an eye movement sample for enrollment. The XORed Biometric template is further secured by multiplication with an identity matrix of size (n × n). These results show positive feedback on this model as individuals can be uniquely identified by their eye movement features. The use of hamming distance as additional verification helper increased model performance significantly. The proposed scheme has a 37% FRR and a 27% FAR based on the 400 trials, which are very promising results for future improvements.