Tracking Eye Movements Research Articles

Characteristics of Visual Cognition in Patients with Anoxic Encephalopathy: An Eye-tracking Study.

: Despite the frequent occurrence of visual cognitive impairment after anoxic encephalopathy, only a few studies have analyzed gaze movements following encephalopathy. This study determined the visual cognitive characteristics of patients with anoxic encephalopathy using an eye-tracking system. : This study included ten patients with anoxic encephalopathy and ten age/sex-matched controls. Factors for anoxic encephalopathy onset and brain imaging findings were extracted from medical records. An eye-tracking system was used to track eye movements during three visual search tasks (pop-out, serial search, and saliency) in patient and healthy control groups. The average target search time, number of saccades, and number of fixations to salient stimuli were compared. : Stagnant blood flow, observed in six of ten patients, was the most common cause of disease onset, four of whom exhibited hypoperfusion in bilateral occipital or parietal lobes on single-photon emission computed tomography. The patient group required longer search times during all visual search tasks and a higher number of saccades during pop-out and serial search tasks. However, no significant difference was observed between the two groups for the number of fixations to salient stimuli during the saliency task. : Following anoxic encephalopathy, bottom-up (pop-out task) and top-down (serial search task) gaze control were considered impaired because of extensive parieto-occipital lobe damage after blood flow stagnation. Patients exhibited reduced top-down function for finding targets (serial search task) but relatively retain inhibitory function for salient stimuli (saliency task). Gaze analysis can be used to reveal the clinical characteristics of anoxic encephalopathy.

Eye-Tracking System with Low-End Hardware: Development and Evaluation

Eye-tracking systems have emerged as valuable tools in various research fields, including psychology, medicine, marketing, car safety, and advertising. However, the high costs of the necessary specialized hardware prevent the widespread adoption of these systems. Appearance-based gaze estimation techniques offer a cost-effective alternative that can rely solely on RGB cameras, albeit with reduced accuracy. Therefore, the aim of our work was to present a real-time eye-tracking system with low-end hardware that leverages appearance-based techniques while overcoming their drawbacks to make reliable gaze data accessible to more users. Our system employs fast and light machine learning algorithms from an external library called MediaPipe to identify 3D facial landmarks. Additionally, it uses a series of widely recognized computer vision techniques, like morphological transformations, to effectively track eye movements. The precision and accuracy of the developed system in recognizing saccades and fixations when the eye movements are mainly horizontal were tested through a quantitative comparison with the EyeLink 1000 Plus, a professional eye tracker. Based on the encouraging registered results, we think that it is possible to adopt the presented system as a tool to quickly retrieve reliable gaze information.

Eye Motion Tracking for Medical Image Interpretation Training.

The significance of Eye Motion Tracking in aiding learners in training search patterns, pattern recognition, and efficiently using their gaze in terms of time and scanning distribution has been highlighted in the USAF Pilot Training Next initiative. The innovation described further builds on this concept in the realm of medical imaging and the provision of real-time feedback of eye direction and gaze duration. This real-time indicator enables the trainer to adapt verbal queueing of the trainee in a personalized manner to improve knowledge transfer, and to increase the confidence of the trainer and trainee in the competency of the trainee. The initial experiment data set included bone radiographs, digital subtraction angiograms, and computed tomography images. Preliminary results and formative feedback from participants was encouraging with expert viewers able to use Eye Motion Tracking to successfully guide novice readers through search and gaze protocol patterns of the medical images.

Tracking a moving visual target in the rhesus monkey: influence of the occurrence frequency of the target path.

Following previous studies documenting the ability to generate anticipatory responses, we tested whether the repeated motion of a visual target along the same path affected its oculomotor tracking. In six rhesus monkeys, we evaluated how the frequency of a target path influenced the onset, accuracy, and velocity of eye movements. Three hundred milliseconds after its extinction, a central target reappeared and immediately moved toward the periphery in four possible (oblique) directions and at a constant speed (20°/s or 40°/s). During each daily session, the frequency of one motion direction was either uncertain (25% of trials) or certain (100% of trials). Our results show no reduction of saccade latency between the two sessions. No express saccades were observed in either session. A slow eye movement started after target onset (presaccadic glissade) and its velocity was larger during the "certain" sessions only with the 40°/s target. No anticipatory eye movement was observed. Longer intersaccadic intervals were found during the "certain" sessions but the postsaccadic pursuit velocity exhibited no change. No correlation was found between the accuracy and precision of saccades (interceptive or catch-up) and the postsaccadic pursuit velocity. Repeatedly tracking a target that moves always along the same path does not favor the generation of anticipatory eye movements, saccadic or slow. Their occurrence is not spontaneous but seems to require preliminary training. Finally, for both sessions, the lack of correlation between the saccade-related and pursuit-related kinematic parameters is consistent with separate control of saccadic and slow eye movements.NEW & NOTEWORTHY Following previous studies documenting anticipatory movements, we investigated how the frequency of occurrence of a target path influenced the generation of tracking eye movements. When present, the effects were small. The limited performance that we found suggests that anticipatory responses require preliminary training, in which case, they should not be considered as a behavioral marker of the primates' ability to extrapolate but the outcome of learning and remembering past experience.

Tracking gaze position from EEG: Exploring the possibility of an EEG-based virtual eye-tracker.

Ocular artifact has long been viewed as an impediment to the interpretation of electroencephalogram (EEG) signals in basic and applied research. Today, the use of blind source separation (BSS) methods, including independent component analysis (ICA) and second-order blind identification (SOBI), is considered an essential step in improving the quality of neural signals. Recently, we introduced a method consisting of SOBI and a discriminant and similarity (DANS)-based identification method, capable of identifying and extracting eye movement-related components. These recovered components can be localized within ocular structures with a high goodness of fit (>95%). This raised the possibility that such EEG-derived SOBI components may be used to build predictive models for tracking gaze position. As proof of this new concept, we designed an EEG-based virtual eye-tracker (EEG-VET) for tracking eye movement from EEG alone. The EEG-VET is composed of a SOBI algorithm for separating EEG signals into different components, a DANS algorithm for automatically identifying ocular components, and a linear model to transfer ocular components into gaze positions. The prototype of EEG-VET achieved an accuracy of 0.920° and precision of 1.510° of a visual angle in the best participant, whereas an average accuracy of 1.008°±0.357° and a precision of 2.348°±0.580° of a visual angle across all participants (N=18). This work offers a novel approach that readily co-registers eye movement and neural signals from a single-EEG recording, thus increasing the ease of studying neural mechanisms underlying natural cognition in the context of free eye movement.

Presenting points or rank: The impacts of leaderboard elements on English vocabulary learning through video lectures

AbstractBackgroundLeaderboards are a highly popular gamification component used in student learning to enhance motivation, attentional engagement, and learning performance. However, few studies have examined the effects of individual leaderboard elements on English vocabulary learning through video lectures.ObjectivesThe present study aimed to examine how different leaderboard elements (i.e., points and rank) may affect students' English vocabulary learning through video lectures.MethodsA total of 34 students were assigned to groups using different leaderboard elements in a counterbalanced order. Participants' motivation, eye movements, and learning performance were measured and analysed.Results and ConclusionsStudents' leaderboard rank was shown to increase their motivation regardless of whether other elements were present. Eye movement tracking revealed that the presence of the leaderboard increased students' saccades between the questions and the options, and lengthened their dwell time on the learning materials while reducing their dwell time on the non‐learning‐related screen areas. Presenting students' rank alone also improved their learning performance.ImplicationsOur findings strongly support the use of video lectures for English vocabulary learning, with the following recommendations: (1) Instructors should present students' rank on the leaderboard to enhance students' motivation and engagement; (2) Instructors should present only the students' rank on the leaderboard to also enhance students' learning performance.

Oculomotor analysis to assess brain health: preliminary findings from a longitudinal study of multiple sclerosis using novel tablet-based eye-tracking software.

A growing body of evidence supports the link between eye movement anomalies and brain health. Indeed, the oculomotor system is composed of a diverse network of cortical and subcortical structures and circuits that are susceptible to a variety of degenerative processes. Here we show preliminary findings from the baseline measurements of an ongoing longitudinal cohort study in MS participants, designed to determine if disease and cognitive status can be estimated and tracked with high accuracy based on eye movement parameters alone. Using a novel gaze-tracking technology that can reliably and accurately track eye movements with good precision without the need for infrared cameras, using only an iPad Pro embedded camera, we show in this cross-sectional study that several eye movement parameters significantly correlated with clinical outcome measures of interest. Eye movement parameters were extracted from fixation, pro-saccade, anti-saccade, and smooth pursuit visual tasks, whereas the clinical outcome measures were the scores of several disease assessment tools and standard cognitive tests such as the Expanded Disability Status Scale (EDSS), Brief International Cognitive Assessment for MS (BICAMS), the Multiple Sclerosis Functional Composite (MSFC) and the Symbol Digit Modalities Test (SDMT). Furthermore, partial least squares regression analyses show that a small set of oculomotor parameters can explain up to 84% of the variance of the clinical outcome measures. Taken together, these findings not only replicate previously known associations between eye movement parameters and clinical scores, this time using a novel mobile-based technology, but also the notion that interrogating the oculomotor system with a novel eye-tracking technology can inform us of disease severity, as well as the cognitive status of MS participants.

A local optical flow eye-tracking method for depression detection

Aiming at the problem that depression detection is easily affected by subjective factors such as patient willingness, self-awareness, and doctor’s level, as well as inconvenient detection and high cost, a universal detection method with low cost and convenient deployment is proposed. A local optical flow tracking method is adopted, which is realized by eye region detection and optical flow estimation. Then, three experiments are designed to verify the accuracy of the method and the effectiveness of eye movement tracking. The formula for calculating the depression state is proposed, and the eye movement of one normal participant’s elliptical trajectory of the left and right pupils in the horizontal and vertical directions is 44.4805, 42.7013, 29.3571, and 31.1364 mm, respectively. To verify the effectiveness of the proposed method, three example points are selected. Among them, the fixation duration at P1 is 1.87 s, the eye movement direction at P2 and P3 is 1.168°, counterclockwise around the X axis, and the number of fixation times is 46. Finally, 18 normal participants and four depression-positive participants are tested by the exploratory eye movement paradigm. The results show that the accuracy rate of identifying depression patients using the NEF metric method can reach ∼81.8%, which can help quantify the detection of depression and provide the possibility for professionals to remotely diagnose individuals with depression.

Facial affect recognition in context in adults with and without TBI.

Several studies have reported impaired emotion recognition in adults with traumatic brain injury (TBI), but studies have two major design features that limit application of results to real-world contexts: (1) participants choose from among lists of basic emotions, rather than generating emotion labels, and (2) images are typically presented in isolation rather than in context. To address these limitations, we created an open-labeling task with faces shown alone or in real-life scenes, to more closely approximate how adults with TBI label facial emotions beyond the lab. Participants were 55 adults (29 female) with moderate to severe TBI and 55 uninjured comparison peers, individually matched for race, sex, and age. Participants viewed 60 photographs of faces, either alone or in the pictured person's real-life context, and were asked what that person was feeling. We calculated the percent of responses that were standard forced-choice-task options, and also used sentiment intensity analysis to compare verbal responses between the two groups. We tracked eye movements for a subset of participants, to explore whether gaze duration or number of fixations helped explain any group differences in labels. Over 50% of responses in both groups were words other than basic emotions on standard affect tasks, highlighting the importance of eliciting open-ended responses. Valence of labels by participants with TBI was attenuated relative to valence of Comparison group labels, i.e., TBI group responses were less positive to positive images and the same was true for negative images, although the TBI group responses had higher lexical diversity. There were no significant differences in gaze duration or number of fixations between groups. Results revealed qualitative differences in affect labels between adults with and without TBI that would not have emerged on standard forced-choice tasks. Verbal differences did not appear to be attributable to differences in gaze patterns, leaving open the question of mechanisms of atypical affect processing in adults with TBI.

Eye Movement Tracking Using Opencv Python

In this study, we made a simple, low-cost algorithm for tracking eye movements and eye blinks in real-time and non-real-time. Several methods are being used right now. Show parts of the face, like the eyes or the whole face. For this reason, open-source libraries like OpenCV enable high-level programming to implement reliable and accurate detection algorithms like Haar Cascade. Since everything is processed in real-time, payment must be made quickly. Pay attention to how hardware, like a computer, can only use a certain amount of resources (processing power). The system has been proven to work by tests with 15 people of different ages and backgrounds. These tests are done to see how the user and the device work together and ensure everything works correctly. The In the tests done, the system worked between 80% and 100% of the time. The results showed that Haar Cascade had a significant effect by Detection of faces in 100% of cases, while the eyes and pupil where they overlap (light and shade) is less effective. In addition to looking at how well the Through these activities, the demo application also showed that user restrictions shouldn't stop people from enjoying and using a certain type of technology. The program was written in C++, and the OpenCV library makes it work on Windows. This system has many uses in the real world and science. By looking at the data from this algorithm from afar, for example, it can tell if someone has an eye disease or is tired. It can also help people who have physical or mental problems

Predictive Eye Movements Characterize Active, Not Passive, Participation in the Collective Embodied Learning of a Scientific Concept

Embodied pedagogy maintains that teaching and learning abstract concepts can benefit significantly from integrating bodily movements into the process. However, the dynamics of such an integration, as well as its dependency on active participation, are not known. Here, we examined the dynamics of visual perception loops during embodied training by tracking eye movements during a session of the collective embodied learning of a concept in physics—angular velocity. Embodied learning was accomplished by the subjects, forming a line that rotated around a central object, in this case, a bottle. We tracked the gaze resulting from the eye and head movements in 12 subjects, who both actively participated in the collective embodied exercise and passively watched it. The tracking data of 7 of these 12 subjects passed our tracking reliability criteria in all the trials and are reported here. During active learning, the learners tended to look ahead of the rotating line (by 35.18 ± 14.82 degrees). In contrast, while passively watching others performing the task, the learners tended to look directly at the line. Interestingly, while the learners were performing the collective exercise, they were unaware of looking ahead of the rotating line. We concluded that the closed-loop perceptual dynamics differed between the active and passive modes, and discussed possible consequences of the observed differences with respect to embodied pedagogy.

A Comprehensive Situation Awareness Measurement Method for Analyzing the Operators’ Situation Awareness of Multi-Module High Temperature Gas-Cooled Reactor Plants

For multi-modular nuclear power plants under the scheme of multiple nuclear steam supply system (NSSS) modules driving a single steam turbine, the NSSS modules are coupled tightly with each other by the common turbine, giving more complex normal operation with respect to the single-modular plants. To limit the operation cost of multi-modular plants, one operator is assigned to monitor and control two or more modules, whose feasibility should be verified. Combined with the characteristics of multi-module control rooms and multi-module running tasks, this paper designs a comprehensive situation awareness measurement method that combines SART, NASA-TLX (NASA Task Load Index), and eye movement tracking methods. The SART, NASA-TLX, and gaze entropy are adopted to measure the operators’ SA, and a series of accident handling experiments are performed on a full-scale simulator to gain enough data for analysis. The operators’ eye trajectories on the human–machine interface (HMI) during the experiments are all recorded for calculating the gaze entropy. Both the SART and NASA-TLX scales are filled by the operators after finishing the experiments. The experiment results show that the difference in operators’ workload and SA amongst all the experimental scenarios is limited, even between the toughest and tenderest scenarios, indicating the feasibility of one operator driving two NSSS modules simultaneously.

Quantitative Model Study of the Psychological Recovery Benefit of Landscape Environment Based on Eye Movement Tracking Technology

From the perspective of landscape and human health, we use the Self-Rating Restoration Scale (SRRS) as a tool to explore the mental health restoration benefits brought by a landscape environment to individuals and explore the characteristics of individual movement behavior when viewing the landscape through the eye movement tracking technology. We selected average blink duration, average gaze length, average saccade amplitude, blink number, number of fixation points, saccade number, and average pupil diameter as experimental indicators for data monitoring. Based on the eye movement heat map obtained by data visualization processing and the results of correlation analysis, we summarized the eye movement behavior characteristics of individuals when viewing the restorative landscape. We try to construct a quantitative evaluation model of the landscape mental recovery benefit with the objective eye movement index as the independent variable through the method of curve estimation. The study results show that individual eye movement behavior is related to the landscape type and the level of psychological recovery is also different. (1)The more singular that the constituent elements are, the more widespread and concentrated the regional distribution of individual attention areas, and the relative psychological recovery benefit is relatively weak. The more complex that the constituent elements are, the more scattered and smaller the individual interest area, and the psychological recovery benefit is better. Brightly colored, dynamic landscapes are easier to form areas of interest to improve the psychological response to the human body. (2) The psychological recovery benefit of the landscape is directly proportional to the changing trend of the average blink duration, number of fixation points, and number of saccades and is inversely proportional to the changing trend of the average gaze length. (3) The objective eye movement index of average blink duration can quantitatively predict the psychological recovery benefit value of the landscape environment. The number of fixation points, the number of saccades, and the average fixation length could predict the psychological recovery benefits of the landscape, while the other indicators had no prediction effect.

A-41 The Use of Virtual Reality for the Diagnosis of Pediatric Sports-Related Concussion: A Feasibility Study

Abstract Purpose Virtual Reality (VR) based concussion software has shown potential in diagnosing sports-related concussion (SRC). The purpose of this study was to explore potential symptom provocation when using a VR based diagnostic concussion software among SRC patients. Methods Pediatric SRC patients aged 12-18 and within 72 hours from injury to initial visit were recruited. While wearing the VR device, patients were instructed to fixate gaze on various targets to track eye movements in a gamified manner. The Post-Concussive Symptom Scale (PCSS) and Virtual Reality Sickness Questionnaire (VRSQ) were administered on a scale of 0 (none) to 3 (severe). Results A total of 21 patients were eligible (Age=14.9±1.7; Female 57.1%; White 61.9%). Patients noted minimal to no symptoms in terms of discomfort (.48±.60), fatigue (.48±.68), headache (1.48±.60), eye strain (.90±.77), inattention (.38±.59), blurred vision (.29±.64), and dizziness (.71±.56) while completing the VR task. Conclusions Compared to other studies using VRSQ among healthy subjects, our sample of acutely injured children with SRC reported minimally provoked symptoms that were below empirically established limits. Specifically, both components of the VRSQ (ocular component MOcu=3.24, SD=1.89; disorientation component MDis=2.59, SD=2.27) ranked below the average limit compared to other studies using VRSQ (MOcu=6.7; MDis=5.8). Future research should gather validity and reliability data to establish the clinical environment in which to diagnose pediatric SRC.

The Development of a Video-based Nutrition Education Curriculum for Patients Undergoing Radical Cystectomy.

The treatment for patients with muscle-invasive bladder cancer includes neoadjuvant chemotherapy followed by radical cystectomy. The American Urological Association guidelines stress the optimization of patient performance status in the perioperative setting. Therefore, implementation of nutrition education is critical for the multi-disciplinary care of this vulnerable patient population and wide distribution of information is critical. The goal of our study was to create a nutrition-based video education series for patients undergoing chemotherapy and radical cystectomy for bladder cancer. Scripts for the videos were developed through an iterative process by experts in nutrition, urology, and communication. Providers and patient advocates were recruited to perform semi-structured interviews and surveys for additional feedback. Performer facial emotion recognition (Noldus™) was used to assess displayed emotion by the presenters. Mangold VisionPlayer software was used for participant eye movement tracking of the video content. A knowledge survey was created, and Item Content Validity Index (I-CVI) was calculated with a nutrition expert advisory board. Participants were recruited for cognitive interviewing to understand the mental processes and interpretations while answering questions. The video series is available to the public on the Bladder Cancer Advocate Network (BCAN) website at the following URL: https://bcan.org/facing-bladder-cancer/nutrition-bladder-cancer/eating-healthy-bladder-cancer/. Cinematic filming methods, (smaller depth of field, lighting, and camera movement) enhanced message delivery along with music and text on screen to anchor important concepts. This study can be a framework for the development of a patient education video library accessible through electronic medical records, health care applications, and patient advocacy websites.

Detection of Attention Deficit/Hyperactivity Disorder (ADHD)

Abstract: In recent years, Machine Learning has had a huge impact on a range of technological disciplines. As technology expands, machine learning provides an exciting opportunity in health care to help medical professionals care for patients and manage clinical data. It improves the accuracy of diagnoses, personalize health care, and find novel solutions to decades-old problems. Hospitals and health care companies have begun to recognize the ability of machine learning to improve decisionmaking and reduce risk in the medical field, which has led to several new and exciting career opportunities. Attention Deficit/Hyperactivity Disorder (ADHD) is a chronic condition generally characterized by hyperactivity, impulsiveness, and difficulty in paying attention. The early diagnosis of ADHD is highly desirable, and there is a need for developing assistive tools to support the diagnosis process in this regard. At present, there are two main methods available - using fMRI data and tracking eye movements. The proposed approach offers a method to assist with the ADHD diagnosis with an emphasis on young children who are still in the early stages of development. It tries to discover the eye-tracking patterns of ADHD using machine learning. The fundamental concept is to convert eye-tracking scan-paths into a visual representation, thus the diagnosis may be viewed as an image classification task.

Concept of Virtual Reality Training of Facility Management Employees Using Eye Tracking

In facility management, employees’ unique skills and high technical knowledge are necessary to operate buildings efficiently and safely. Employees acquiring professional skills requires the use of an effective training procedure. Traditional facility management training is often challenging because it requires using real devices in a work environment. It is only sometimes possible to stop these devices. Additionally, there is a risk of equipment damage or injury to employees. Therefore, organizing staff training in virtual reality (VR) seems interesting. Properly conducted training of employees in virtual reality allows for the reconstruction of identical test conditions for all participants, thanks to which high comparability of training results is achieved. In addition, virtual training allows for an in-depth analysis of each participant’s results. We can carefully analyze their movement, how they perform a task, and even their attention directed to critical elements. To be able to perform such an in-depth analysis, it was proposed to use eye-tracking technology in the VR glasses used during training and evaluation in the VR environment. Eye movement tracking allows for an accurate analysis of the focus of each participant on the critical elements of the devices in the decision-making process. It enables obtaining much more comprehensive information on the concentration and correctness of the employee’s actions. The result of the conducted research is the development of the concept of a VR environment for training and evaluating facility management staff using eye-tracking technology, enabling employees to improve and verify their qualifications in a very comfortable way without the need to access the existing infrastructure. The developed training procedure also allows the classification of training participants as fast and slow learners, which is very important for the employer, as it identifies employees who require additional training support. The developed approach was verified during the realization of selected training conducted with 100 employees working in facility management and was implemented as a commercially offered training service.

An arrayed optofluidic system for three-dimensional (3D) focal control via electrowetting.

A new lens capability for three-dimensional (3D) focal control is presented using an optofluidic system consisting of n × n arrayed liquid prisms. Each prism module contains two immiscible liquids in a rectangular cuvette. Using the electrowetting effect, the shape of the fluidic interface can be rapidly adjusted to create its straight profile with the prism's apex angle. Consequently, an incoming ray is steered at the tilted interface due to the refractive index difference between two liquids. To achieve 3D focal control, individual prisms in the arrayed system are simultaneously modulated, allowing incoming light rays to be spatially manipulated and converged on a focal point located at Pfocal (fx, fy, fz) in 3D space. Analytical studies were conducted to precisely predict the prism operation required for 3D focal control. Using three liquid prisms positioned on the x-, y-, and 45°-diagonal axes, we experimentally demonstrated 3D focal tunability of the arrayed optofluidic system, achieving focal tuning along lateral, longitudinal, and axial directions as wide as 0 ≤ fx ≤ 30 mm, 0 ≤ fy ≤ 30 mm, and 500 mm ≤ fz ≤ ∞. This focal tunability of the arrayed system allows for 3D control of the lens's focusing power, which could not be attained by solid-type optics without the use of bulky and complex mechanical moving components. This innovative lens capability for 3D focal control has potential applications in eye-movement tracking for smart displays, autofocusing of smartphone cameras, or solar tracking for smart photovoltaic systems.

Increasing the Social Interaction of Autism Child using Virtual Reality Intervention (VRI)

Nowadays there is an increase in number of autisms, a neuro-developmental disorder across the world. The level of autism varies with the symptoms such as inattention, interaction, social communication, repetitive behaviors, irritability and the like. Early recovery of a child from autism is necessary to live in a normal socio-communicable life. To measure the inattention of the autism child by enhancing the visual perception through virtual environment. The proposed Virtual Reality Intervention (VRI) enhances visual perception, learning, and social interaction. The proposed method observes the attention level of the autism child through eye tracking or eye movements who interacts with virtual world using eye tracking methodology. As eye tracking is the major component to measure the reduced looking time of objects and subjects which considered being the earliest signs of autism spectrum disorder (ASD). For observing the attention of kids during testing, Eye movements and gestures plays a major role. Using head position and eye pupil direction, attention has been analyzed. Quantitative and Qualitative findings conclude that the inattention of autism child can gradually be reduced by iterating the virtual therapy through eye ball tracking technique. Qualitative finding is done using Aberrant Behavior Checklist (ABC) and quantitative using eye-pupil and head position. Autism affected children can easily recovered from this inattention symptom by continuous iterations on virtual therapy. Similar virtual therapies can also be provided to address other symptoms of autism.

Tracking Eye Movements as a Window on Language Processing: The Visual World Paradigm

This entry overviews the pioneering experimental studies exploiting eye movement data to investigate language processing in real time. After examining how vision and language were found to be closely related, herein focus the discussion on the evolution of eye-tracking methodologies to investigate children’s language development. To conclude, herein provide some insights about the use of eye-tracking technology for research purposes, focusing on data collection and data analysis.