Eye-tracking Technology Research Articles

Exploring the differences between landscape colour and perceptive colour when walking through urban green space in summer

Landscape colour influences people’s visual behaviour and preferences. Insufficient exploration has been conducted on people’s colour perception when walking through urban green spaces (UGSs) dominated by green in summer. This study used eye-tracking technology to explore the differences between the visual attention colour (VAC) and space colour (SC), and the effect of spatial form on VAC. Participants were asked to view six walking spaces in two UGSs in Nanjing, China. The results indicated that SC and VAC had correlations in hue variance (yellow), saturation mean, and value variance, but weak correlations in hue mean (green), hue variance (green), and value mean. Additionally, the higher the spatial openness, the more reduction in brightness of the VAC compared to SC. The findings suggest that landscape visual perception studies need to consider the interaction between landscape colour, spatial form, and human top-down visual behaviour to support the design of UGSs.

Real-time Prediction of Students' Math Difficulties using Raw Data from Eye Tracking and Neural Networks

Eye tracking technology in adaptive learning systems enhances diagnostic capabilities by providing valuable insights into cognitive processes. This information can be leveraged to identify and address difficulties. So far, there have been only few attempts of realizing this. Studies are usually only about recognizing correctness of answers and the evaluation is complex and difficult to transfer due to features depending on Areas of Interests (AOIs). We close this gap and present a time-dynamic approach to identify specific difficulties based on raw gaze data. The eye tracking data of 139 students while solving a math problem serve as a sample. Difficulties that arose during the solution process are known. A temporal convolutional network (TCN) is trained to perform a multiclass classification on sequential data. On this basis we present an algorithm which simulates a dynamic classification in an adaptive real-time system. We evaluate this procedure achieving an accuracy of almost 80%.

Investigation of user-product interaction by determining the focal points of visual interest in different types of kitchen furniture: An eye-tracking study

The furniture industry faces the challenge of designing furniture that attracts greater visual attention from customers, leading to increased sales and positive impacts on the industry, businesses, economy, and the environment. In pursuit of this objective, the imperative lies in the development of user-centric designs that amplify the interaction between users and products within the furniture sector. This research aims to identify the focal points of interest in kitchen furniture through the utilization of eye-tracking technology. By analyzing the gaze points of 60 participants observing 10 different kitchen furniture models introduced in the showroom, valuable insights can be provided to designers. These insights, in turn, empower designers to fabricate products that effectively capture heightened user attention. The investigation involves the assessment of average gaze counts and the generation of visual interest heatmaps. The discernments derived from the research underscore that areas at eye level garner a more pronounced level of attention. Furthermore, the study observes that factors such as material diversity, accessory utilization, and the integration of lighting elements exert a positive influence on visual interest. The results, within the context of neurodesign, offer valuable guidance to the furniture sector. These results can support decision-making in new product design, manufacturing, and marketing, enabling the industry to produce attention-grabbing furniture.

Effect of interface design on cognitive workload in unmanned aerial vehicle control

Unmanned Aerial Vehicle (UAV) control interfaces are critical channels for transferring information between the vehicle and an operator. Research on system performance has focused on enhancing vehicle automation and some work has evaluated cognitive workload for existing UAV interfaces. The potential for usable interface design to reduce cognitive workload during the early design phase has been largely overlooked. This study addresses these gaps by: (1) evaluating the effectiveness of a contemporary UAV interface design tool (the Modified GEDIS-UAV) to moderate user workload; (2) examining the effectiveness of various UAV interface designs for minimizing cognitive workload under different control task pacing; and (3) exploring the use of eye tracking measures, traditionally applied in other domains, as indicators of cognitive workload in UAV operations. We prototyped three different interface designs, classified as “baseline”, “enhanced” and “degraded” interfaces. Cognitive workload in UAV operation was manipulated in terms of levels of vehicle speed (“low” and “high”). Physiological and subjective measures of workload were collected for all combinations of interface design and task demand. Results revealed the “enhanced” interface to yield the lowest operator cognitive workload and supported operator resilience to increased control task demand, as compared to the “baseline” and “degraded” interfaces. In addition, task demand was found to elevate operator cognitive workload, particularly in terms of "mental" and "temporal" demands and operator perceptions of "performance". The study also demonstrated utility of eye-tracking technology for detecting cognitive workload in UAV operations. This research provides practical guidance for UAV control interface design to manage operator workload. The methods employed in the study are applicable to interface evaluation for various types of UAVs and other unmanned systems to enhance human-automation interaction.

Assessing the Legibility of Arabic Road Signage Using Eye Gazing and Cognitive Loading Metrics

This research study aimed to evaluate the legibility of Arabic road signage using an eye-tracking approach within a virtual reality (VR) environment. The study was conducted in a controlled setting involving 20 participants who watched two videos using the HP Omnicept Reverb G2. The VR device recorded eye gazing details in addition to other physiological data of the participants, providing an overlay of heart rate, eye movement, and cognitive load, which in combination were used to determine the participants’ focus during the experiment. The data were processed through a schematic design, and the final files were saved in .txt format, which was later used for data extraction and analysis. Through the execution of this study, it became apparent that employing eye-tracking technology within a VR setting offers a promising method for assessing the legibility of road signs. The outcomes of the current research enlightened the vital role of legibility in ensuring road safety and facilitating effective communication with drivers. Clear and easily comprehensible road signs were found to be pivotal in delivering timely information, aiding navigation, and ultimately mitigating accidents or confusion on the road. As a result, this study advocates for the utilization of VR as a valuable platform for enhancing the design and functionality of road signage systems, recognizing its potential to contribute significantly to the improvement of road safety and navigation for drivers.

Eye Tracking Technology

Measurement of eye movement is an activity done with the help of eye tracking technology. In this activity, the movement of pupils is a respond towards the stimuli. It gives information as per the gaze point of the individual person. The biometric tools are used for analysing .[10].ET is being involved with most of the fields which includes HCI, Designs, Medicals, Psychology and Buisness Marketing.[6].This paper gives the explaination and importance of ET in the life of advancement and its history.It starts in the late 19th Century.ET is done by filming of the eye according to its behaviour.This Research Paper includes different types of fields in an explaination manner.It includes the process of how ET helps in Research based on previous evaluations.Eye is generally act as a tool of brain system.ET devices respond to the movement of stimuli

Native advertising on mobile applications: using eye tracking to investigate the effects of advertising format, user motivation, and advertising disclosure on advertising effects

Although native advertising has become the primary advertising type in the mobile application context, few studies have focused on its influential factors. This study uses eye-tracking technology to examine the impacts of ad format, user motivation, and ad disclosure on advertising effects in the Chinese context. Respondents (N = 422) were recruited to participate in a 2 (ad format: statics vs. dynamics) × 2 (user motivation: information-seeking vs. entertainment-seeking) × 2 (ad disclosure: non-disclosed vs. disclosed) between-subjects experiment. The results showed that users with an entertainment-seeking motivation paid greater attention and showed less attitudinal responses to dynamic (vs. static) ads. While no differences were observed in attention duration and attitudinal responses to disclosed dynamic and static ads for users with an information-seeking motivation, these users perceived undisclosed dynamic (vs. static) ads as more intrusive. These findings extend the literature on native advertising to the Chinese mobile media context and offer practical implications for native advertising designs.

Parental narrative style moderates the relation between pain-related attention and memory biases in youth with chronic pain.

Negatively biased pain memories robustly predict maladaptive pain outcomes in children. Both attention bias to pain and parental narrative style have been linked with the development of these negative biases, with previous studies indicating that how parents talk to their child about the pain might buffer the influence of children's attention bias to pain on the development of such negatively biased pain memories. This study investigated the moderating role of parental narrative style in the relation between pain-related attention and memory biases in a pediatric chronic pain sample who underwent a cold pressor task. Participants were 85 youth-parent dyads who reminisced about youth's painful event. Eye-tracking technology was used to assess youth's attention bias to pain information, whereas youth's pain-related memories were elicited 1 month later through telephone interview. Results indicated that a parental narrative style using less repetitive yes-no questions, more emotion words, and less fear words buffered the influence of high levels of youth's attention bias to pain in the development of negatively biased pain memories. Opposite effects were observed for youth with low levels of attention bias to pain. Current findings corroborate earlier results on parental reminiscing in the context of pain (memories) but stress the importance of matching narrative style with child characteristics, such as child attention bias to pain, in the development of negatively biased pain memories. Future avenues for parent-child reminiscing and clinical implications for pediatric chronic pain are discussed.

DPGazeSynth: Enhancing eye-tracking virtual reality privacy with differentially private data synthesis

As spatial computing devices increasingly integrate eye-tracking technology to enhance virtual reality (VR) experiences, the imperative to protect sensitive eye-tracking data against privacy risks, such as user re-identification, has become more pressing. Existing privacy-preserving mechanisms face challenges in balancing the dual demands of privacy and utility in the context of VR applications. This paper presents DPGazeSynth, a novel framework designed to fortify privacy protections while ensuring the utility of eye-tracking data. DPGazeSynth addresses the unique requirements of gaze path synthesis, especially the differentiation between fixations and saccades. Our approach introduces a semi-synthetic method based on the Markov Chain model to accurately maintain data correlations for analytical tasks. We demonstrate that DPGazeSynth provides robust differential privacy guarantees, and our comprehensive experiments on two real-world datasets validate its effectiveness in safeguarding against re-identification attacks. The results showcase DPGazeSynth's better performance over existing solutions like Kalεido and establish its potential as a reliable foundation for future research aimed at reconciling privacy concerns with the demands of complex trajectory data analysis in eye-tracking applications.

Using Eye tracking to Examine Young Adults' Visual Attention to E-cigarette Advertising Features and Associated Positive E-cigarette Perceptions.

Little is known about the influence of e-cigarette marketing features on the antecedents of e-cigarette use. Using an eye-tracking experiment, we examined visual attention to common features in e-cigarette ads and its associations with positive e-cigarette perceptions among young adults. Young adults (ages 18-29) who smoke cigarettes (n = 40) or do not use tobacco (n = 71) viewed 30 e-cigarette ads on a computer screen. Eye-tracking technology measured dwell time (fixation duration) and entry time (time to first fixation) for 14 pre-defined ad features. Participants then completed a survey about perceptions of e-cigarettes shown in the ads. We used regression models to examine the associations between ad features and standardized attention metrics among all participants and by tobacco-use status and person-aggregated standardized attention for each ad feature and positive e-cigarette perceptions. Dwell time was the longest for smoker-targeted claims, positive experience claims, and price promotions. Entry time was the shortest for multiple flavor descriptions, nicotine warnings, and people. Those who do not use tobacco had a longer dwell time for minor sales restrictions and longer entry time for purchasing information than those who smoke. Longer dwell time for multiple flavor descriptions was associated with e-cigarette appeal. A shorter entry time for fruit flavor description was associated with positive e-cigarette-use expectancies. Young adults allocated attention differently to various e-cigarette ad features, and such viewing patterns were largely similar by tobacco-use statuses. Multiple or fruit flavors may be the features that contribute to the positive influence of e-cigarette marketing among young adults.

Urban perception by using eye movement data on street view images

AbstractUnderstanding the spatial distribution patterns of urban perception and analyzing the correlation between human emotional perception and street composition elements are important for accurately understanding how people interact with the urban environment, urban planning, and urban management. Previous studies on urban perception using street view data have not fully considered the actual level of attention to different visual elements when browsing street view images. In this article, we use eye tracking technology to collect eye movement data and subjective perception evaluation data when people browse street view images, and analyze the correlation between the time to first fixation, duration of first fixation, and fixation frequency of different visual elements and the six perceptual outcomes of wealthy, safe, lively, beautiful, boring, and depressing. Furthermore, this article integrates eye movement data with street view semantic data and introduces a novel method for predicting urban perception using a machine learning algorithm. The proposed method outperforms a comparative model that solely relies on semantic data, exhibiting higher accuracy in perception prediction. Additionally, the study presents a perceptual mapping of the prediction results, providing a visual representation of the predicted urban perception outcomes. As vision is the primary perceptual channel, this study achieves a more objective and scientifically reliable urban perception, which is of reference value for the study of physical and mental health due to the urban physical environment.

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.

Comparison of the effectiveness of correcting the sensory perception of skilled tennis players through auditory deprivation and improving the function of the visual analyzer

Introduction. In the context of the need to search for new means and methods of improving the training process of adolescent tennis players, which are practically exhausted in terms of improving physical fitness and technical skills, a significant pedagogical task arises – to identify the possibility of effective influence on the sensory-perceptual processes of athletes as a factor of sensorimotor coordination of motor actions and cognitive functions. The purpose of the article is to determine the effectiveness and expediency of using two approaches to correcting and improving the sensory perception of tennis players aged 17-18 years – the exclusion of an acoustic stimulus during the game or the inclusion of additional means of influencing the visual analyzer. Methods and materials. The study involved tennis players aged 17-18 years with the first sports category, among 28 athletes who were divided into two groups: the first experimental group (EG-1) included 14 young athletes who practiced for 6 weeks (4 classes per week) according to a program based on hearing deprivation in the classroom. The second group, EG-2, was engaged in using special visual exercises as an out-of-training tool. Methods: literature analysis, pedagogical experiment, instrumental methods (Babolat Pure Drive Play, Eye-Tracking technology), questionnaires, methods of mathematical data processing (descriptive statistics, Student's t-test). Results. During the experiment, it was found that a group of tennis players who were engaged in a training program with the exception of hearing (EG-1) showed the best results in all the studied indicators. In particular, statistically significant differences were obtained between the groups in terms of fixation time at the target object, which improved in EG-1 by 33.7-37.8% (t=4.19-4.28, p<0.01), in EG-2 – by 10.7-11.9% (t=3.26-3.38, p<0.01), intergroup differences were established at t=4.65-4.79, p<0.01. Conclusion. The results obtained indicate that the indirect effect on the sensory perception of qualified tennis players through local sensory deprivation of one of the analyzers – acoustic, as a way to create complicated and variable conditions in the mode of a traditional training session, is more effective, expedient and easy to use, compared with the introduction for the same purposes, out-of-training tools, including direct effect on the visual analyzer using special exercises for the eyes.

AI-Assisted Diagnostics in Dentistry: An Eye-Tracking Study on User Behavior.

Artificial Intelligence (AI) has increasingly been integrated into dental practices, notably in radiographic imaging like Orthopantomograms (OPGs), transforming diagnostic protocols. Eye tracking technology offers a method to understand how dentists' visual attention may differ between conventional and AI-assisted diagnostics, but its integration into daily clinical practice is challenged by the cost and complexity of traditional systems. Thirty experienced practitioners and dental students participated to evaluate the effectiveness of two low-budget eye-tracking systems, including the Peye Tracker (Eye Tracking Systems LTD, Southsea, UK) and Webgazer.js (Brown University, Providence, Rhode Island) in a clinical setting to assess their utility in capturing dentists' visual engagement with OPGs. The hardware and software setup, environmental conditions, and the process for eye-tracking data collection and analysis are illustrated. The study found significant differences in eye-tracking accuracy between the two systems, with Webgazer.js showing higher accuracy compared to Peye Tracker (p<0.001). Additionally, the influence of visual aids (glasses vs. contact lenses) on the performance of eye-tracking systems revealed significant differences for both Peye Tracker (p<0.05) and Webgazer.js (p<0.05). Low-budget eye-tracking devices present challenges in achieving the desired accuracy for analyzing dentists' visual attention in clinical practice, highlighting the need for continued innovation and improvement in this technology. Key words:Artificial intelligence, Eye-tracking device, low-budget, dentistry.

안구 입력 시스템 기반의 화상키보드 키 배열 연구

The eyeball input system is a text input system designed based on ‘eye tracking technology' and ‘virtual keyboard character-input technology'. The current virtual keyboard structure used is a rectangular QWERTY array optimized for a multi-input method that simultaneously utilizes all 10 fingers on both hands. However, since ‘eye-tracking technology’ is a single-input method that relies solely on eye movement, requiring only one focal point for input, problems arise when used in conjunction with a rectangular virtual keyboard structure designed for multi-input method. To solve this problem, first of all, previous studies on the shape, type, and movement of muscles connected to the eyeball were investigated. Through the investigation, it was identified that the principle of eye movement occurs in a circle rather than in a straight line. This study, therefore, proposes a new key arrangement wherein the keys are arranged in a circular structure suitable for rotational motion rather than the key arrangement of the current virtual keyboard which is arranged in a rectangular structure and optimized for both-hand input. In addition, compared to the existing rectangular key arrangement, a performance verification experiment was conducted on the circular key arrangement, and through the experiment, it was confirmed that the circular arrangement would be a good replacement for the rectangular arrangement for the virtual keyboard.

Visualizing simultaneous eye-hand movements in a MATLAB dashboard

Eye-hand coordination (EHC) is crucial to our daily activities, and its underlying mechanisms are being intensely studied. The analysis of simultaneous eye and hand movements can provide valuable insights into EHC, particularly for individuals struggling with dexterous control, such as might be caused by stroke or traumatic brain injuries. Despite advancements in motion-capture and eye tracking technologies, there is currently no automated method for visualizing concurrent eye- and hand-movement data. To address this need, we have developed a MATLAB-based dashboard designed for near instantaneous analysis and visualization of eye and hand-tracking data. This paper introduces the design of the dashboard and presents experimental results obtained from its application, leveraging simulated data inspired by our recent work in stroke. This testing suggests that our solution has the potential to significantly aid in understanding and investigating EHC by providing side-by-side and time-locked comparison of eye/hand movements along with their timing and spatio-temporal errors, offering novel opportunities for research and clinical applications.•Continuous eye movement data is collected throughout the experiment•Continuous hand movement data is collected throughout the experiment•Combine datasets and display time-locked eye-hand data in a single dashboard

Area of Interest Tracking Techniques for Driving Scenarios Focusing on Visual Distraction Detection

On-road driving studies are essential for comprehending real-world driver behavior. This study investigates the use of eye-tracking (ET) technology in research on driver behavior and attention during Controlled Driving Studies (CDS). One significant challenge in these studies is accurately detecting when drivers divert their attention from crucial driving tasks. To tackle this issue, we present an improved method for analyzing raw gaze data, using a new algorithm for identifying ID tags called Binarized Area of Interest Tracking (BAIT). This technique improves the detection of incidents where the driver’s eyes are off the road through binarizing frames under different conditions and iteratively recognizing markers. It represents a significant improvement over traditional methods. The study shows that BAIT performs better than other software in identifying a driver’s focus on the windscreen and dashboard with higher accuracy. This study highlights the potential of our method to enhance the analysis of driver attention in real-world conditions, paving the way for future developments for application in naturalistic driving studies.

Gaze Controlled Wheelchair

Abstract: A gaze-controlled wheelchair is an innovative assistive technology designed to empower individuals with mobility impairments. This system utilizes eye-tracking technology to interpret a user’s gaze patterns and translate them into control commands for the wheelchair. By integrating sophisticated sensors and algorithms, the wheelchair can accurately respond to the user’s eye movements, allowing for intuitive navigation. This technology not only enhances the user’s independence but also addresses the challenges faced by those with limited or no use of their limbs. The abstract highlights the potential of gazecontrolled wheelchairs in improving the quality of life for individuals with diverse mobility needs.

Automatic Home Controlling System for Paralyzed Patient using Eye Gestures

Abstract: The system revolutionizes the lives of paralyzed individuals by harnessing the power of eye-tracking technology for seamless control of home appliances. Utilizing OpenCV for robust and real-time eye tracking, the system enables patients to effortlessly interact with their surroundings by focusing on predefined patterns or commands. A user-friendly interface facilitates the establishment of a connection between eye movements and various household devices, including lights, fans, and entertainment systems. This innovative solution empowers individuals with limited mobility to regain independence, simplifying the management of daily routines and living spaces through intuitive gaze-based commands. By providing a novel avenue for communication and control, the system offers paralyzed patients a renewed sense of autonomy, convenience, and improved quality of life.

The Effects of Live Streamer's Facial Attractiveness and Product Type on Consumer Purchase Intention: An Exploratory Study with Eye Tracking Technology.

As a booming branch of online retailing, live-streaming e-commerce can present abundant information dimensions and diverse forms of expression. Live-streaming e-commerce has enabled online retailers to interact with customers face-to-face, resulting in widespread instances of emotional and impulse buying behavior. Prior research in live-streaming e-commerce has suggested that live streamers' characteristics, especially the live streamer's face, can affect customers' purchase intentions. The present research used questionnaire surveys and an eye tracking experiment to investigate the impact of live streamer's facial attractiveness on consumer purchase intention for search-based and experience-based products. The questionnaire survey analyzed 309 valid questionnaires and revealed that attractive faces are the key influencing factor driving consumers' impulse purchase intentions. Moreover, consumers' emotional experience plays a partial mediating role in the process of live streamers' faces influencing purchase intention. The eye tracking experiment further explored the mechanism of a live streamer's facial attractiveness on consumers' purchase intentions of search-based products and experience-based products from the perspective of visual attention by analyzing 64 valid sets of data. The results showed that attractive faces attract more consumers' attention and, therefore, increase their purchase intention. Furthermore, there is a significant interaction between product type, the live streamer's facial attractiveness, and consumers' purchase intentions. In the case of unattractive live streamers, consumers are more likely to buy search-based products than experience-based products, while the purchase intention does not vary between search-based products and experience-based products in the case of attractive live streamers. The present study provides evidence for 'beauty premium' in live-streaming e-commerce and sheds light on the design of the match between live streamers and different types of products.