Journal of Eye Movement Research最新文献

Dyslexia is a neurodevelopmental disorder that impairs reading, affecting 5-17.5% of children and representing the most common learning disability. Individuals with dyslexia experience decoding, reading fluency, and comprehension difficulties, hindering vocabulary development and learning. Early and accurate identification is essential for targeted interventions. Traditional diagnostic methods rely on behavioral assessments and neuropsychological tests, which can be time-consuming and subjective. Recent studies suggest that physiological signals, such as electrooculography (EOG), can provide objective insights into reading-related cognitive and visual processes. Despite this potential, there is limited research on how typeface and font characteristics influence reading performance in dyslexic children using EOG measurements. To address this gap, we investigated the most suitable typefaces for Turkish-speaking children with dyslexia by analyzing EOG signals recorded during reading tasks. We developed a novel deep learning framework, DyslexiaNet, using scalogram images from horizontal and vertical EOG channels, and compared it with AlexNet, MobileNet, and ResNet. Reading performance indicators, including reading time, blink rate, regression rate, and EOG signal energy, were evaluated across multiple typefaces and font sizes. Results showed that typeface significantly affects reading efficiency in dyslexic children. The BonvenoCF font was associated with shorter reading times, fewer regressions, and lower cognitive load. DyslexiaNet achieved the highest classification accuracy (99.96% for horizontal channels) while requiring lower computational load than other networks. These findings demonstrate that EOG-based physiological measurements combined with deep learning offer a non-invasive, objective approach for dyslexia detection and personalized typeface selection. This method can provide practical guidance for designing educational materials and support clinicians in early diagnosis and individualized intervention strategies for children with dyslexia.

Background: Hand-eye coordination is essential for daily functioning and sports performance, but standardized digital protocols for its reliable assessment are limited. This study aimed to evaluate the intra-examiner repeatability and inter-examiner reproducibility of a computerized protocol (COI-SV^®) for assessing hand-eye coordination in healthy adults, as well as the influence of age and sex. Methods: Seventy-eight adults completed four sessions of a computerized visual-motor task requiring rapid and accurate responses to randomly presented targets. Accuracy and response times were analyzed using repeated-measures and reliability analyses. Results: Accuracy showed a small session effect and minor examiner differences on the first day, whereas response times were consistent across sessions. Men generally responded faster than women, and response times increased slightly with age. Overall, reliability indices indicated moderate-to-good repeatability and reproducibility for both accuracy and response time measures. Conclusions: The COI-SV^® protocol provides a robust, objective, and reproducible measurement of hand-eye coordination, supporting its use in clinical, sports, and research settings.

Accurate recognition of basic facial emotions is well documented, yet the mechanisms of misclassification and their relation to gaze allocation remain under-reported. The present study utilized a within-subjects eye-tracking design to examine both accurate and inaccurate recognition of five basic emotions (anger, disgust, fear, happiness, and sadness) in healthy young adults. Fifty participants (twenty-four women) completed a forced-choice categorization task with 10 stimuli (female/male poser × emotion). A remote eye tracker (60 Hz) recorded fixations mapped to eyes, nose, and mouth areas of interest (AOIs). The analyses combined accuracy and decision-time statistics with heatmap comparisons of misclassified versus accurate trials within the same image. Overall accuracy was 87.8% (439/500). Misclassification patterns depended on the target emotion, but not on participant gender. Fear male was most often misclassified (typically as disgust), and sadness female was frequently labeled as fear or disgust; disgust was the most incorrectly attributed response. For accurate trials, decision time showed main effects of emotion (p < 0.001) and participant gender (p = 0.033): happiness was categorized fastest and anger slowest, and women responded faster overall, with particularly fast response times for sadness. The AOI results revealed strong main effects and an AOI × emotion interaction (p < 0.001): eyes received the most fixations, but fear drew relatively more mouth sampling and sadness more nose sampling. Crucially, heatmaps showed an upper-face bias (eye AOI) in inaccurate trials, whereas accurate trials retained eye sampling and added nose and mouth AOI coverage, which aligned with diagnostic cues. These findings indicate that the scanpath strategy, in addition to information availability, underpins success and failure in basic-emotion recognition, with implications for theory, targeted training, and affective technologies.

In safety-critical systems like nuclear power plants, the rapid and accurate perception of visual interface information is vital. This study investigates the relationship between visual attention dispersion measured via heatmap entropy (as a specific measure of gaze entropy) and response time during information search tasks. Sixteen participants viewed a prototype of an accident response support system and answered questions at three difficulty levels while their eye movements were tracked using Tobii Pro Glasses 2. Results showed a significant positive correlation (r = 0.595, p < 0.01) between heatmap entropy and response time, indicating that more dispersed attention leads to longer task completion times. This pattern held consistently across all difficulty levels. These findings suggest that heatmap entropy is a useful metric for evaluating user attention strategies and can inform interface usability assessments in high-stakes environments.

Purpose: To investigate the efficacy of a novel test for diagnosing colour vision deficiencies using reflexive eye movements measured using an unmodified tablet.

Methods: This study followed a cross-sectional design, where thirty-three participants aged between 17 and 65 years were recruited. The participant group comprised 23 controls, 8 deuteranopes, and 2 protanopes. An anomaloscope was employed to determine the colour vision status of these participants. The study methodology involved using an Apple iPad Pro's built-in eye-tracking capabilities to record eye movements in response to coloured patterns drifting on the screen. Through an automated analysis of these movements, the researchers estimated individuals' red-green equiluminant point and their equivalent luminance contrast.

Results: Estimates of the red-green equiluminant point and the equivalent luminance contrast were used to classify participants' colour vision status with a sensitivity rate of 90.0% and a specificity rate of 91.30%.

Conclusions: The novel colour vision test administered using an unmodified tablet was found to be effective in diagnosing colour vision deficiencies and has the potential to be a practical and cost-effective alternative to traditional methods. Translation Relevance: The test's objectivity, its straightforward implementation on a standard tablet, and its minimal requirement for patient cooperation, all contribute to the wider accessibility of colour vision diagnosis. This is particularly advantageous for demographics like children who might be challenging to engage, but for whom early detection is of paramount importance.

This study investigated how simulated ophthalmic visual field deficits affect visual attention and economic information processing. Using webcam-based eye tracking, 227 participants with normal vision recruited through Amazon Mechanical Turk were assigned to control, central vision loss, peripheral vision loss, or scattered vision loss simulation conditions. Participants viewed economic stimuli of varying complexity while eye movements, cognitive load, and comprehension were measured. All deficit conditions showed altered oculomotor behaviors. Central vision loss produced the most severe impairments: 43.6% increased fixation durations, 68% longer scanpaths, and comprehension accuracy of 61.2% versus 87.3% for controls. Visual deficits interacted with information complexity, showing accelerated impairment for complex stimuli. Mediation analysis revealed 47% of comprehension deficits were mediated through altered attention patterns. Cognitive load was significantly elevated, with central vision loss participants reporting 84% higher mental demand than controls. These findings demonstrate that visual field deficits fundamentally alter economic information processing through both direct perceptual limitations and compensatory attention strategies. Results demonstrate the feasibility of webcam-based eye tracking for studying simulated visual deficits and suggest that different types of simulated visual deficits may require distinct information presentation strategies.

In recent years, Bionic reading has been introduced as a means to combat superficial reading and low comprehension rates. This paper investigates eye movements between participants who read a passage in standard font and an additional Bionic font passage. It was found that Bionic font does not significantly change eye movements when reading. Fixation durations, number of fixations and reading speeds were not significantly different between the two formats. Furthermore, fixations were spread throughout the word and not only on leading characters, even when using Bionic font; hence, participants were not able to "auto-complete" the words. Additionally, Bionic font did not facilitate easier processing of low-frequency or unfamiliar words. Overall, it would appear that Bionic font, in the short term, does not affect reading. Further investigation is needed to determine whether a long-term intervention with Bionic font is more meaningful than standard interventions.

Studies on the relationship between age and situation model updating during narrative text reading have mainly used response or reading times. This study enhances previous measures (working memory, recognition probes, and comprehension) by incorporating eye-tracking techniques to compare situation model updating between young and older Chilean adults. The study included 82 participants (40 older adults and 42 young adults) who read two narrative texts under three conditions (no shift, spatial shift, and character shift) using a between-subject (age) and within-subject (dimensional change) design. The results show that, while differences in working memory capacity were observed between the groups, these differences did not impact situation model comprehension. Younger adults performed better in recognition tests regardless of updating conditions. Eye-tracking data showed increased fixation times for dimensional shifts and longer reading times in older adults, with no interaction between age and dimensional shifts.

Eye tracking, a fundamental process in gaze analysis, involves measuring the point of gaze or eye motion. It is crucial in numerous applications, including human-computer interaction (HCI), education, health care, and virtual reality. This study delves into eye-tracking concepts, terminology, performance parameters, applications, and techniques, focusing on modern and efficient approaches such as video-oculography (VOG)-based systems, deep learning models for gaze estimation, wearable and cost-effective devices, and integration with virtual/augmented reality and assistive technologies. These contemporary methods, prevalent for over two decades, significantly contribute to developing cutting-edge eye-tracking applications. The findings underscore the significance of diverse eye-tracking techniques in advancing eye-tracking applications. They leverage machine learning to glean insights from existing data, enhance decision-making, and minimize the need for manual calibration during tracking. Furthermore, the study explores and recommends strategies to address limitations/challenges inherent in specific eye-tracking methods and applications. Finally, the study outlines future directions for leveraging eye tracking across various developed applications, highlighting its potential to continue evolving and enriching user experiences.

Fixational saccadic eye movements (microsaccades) have been associated with cognitive processes, especially in tasks requiring spatial attention and memory. Alterations in oculomotor and cognitive control are commonly observed in Parkinson's disease (PD), though it is unclear to what extent microsaccade activity is affected. We acquired eye movement data from sixteen participants with early-stage PD and thirteen older healthy controls to examine the effects of dopamine modulation on microsaccade activity during the delay period of a spatial working memory task. Some microsaccade characteristics, like amplitude and duration, were moderately larger in the PD participants when they were "on" their dopaminergic medication than healthy controls, or when they were "off" medication, while PD participants exhibited microsaccades with a linear amplitude-velocity relationship comparable to controls. Both groups showed similar microsaccade rate patterns across task events, with most participants showing a horizontal bias in microsaccade direction during the delay period regardless of the remembered target location. Overall, our data suggest minimal involvement of microsaccades during visuospatial working memory maintenance under conditions without explicit attentional cues in both subject groups. However, moderate effects of PD-related dopamine deficiency were observed for microsaccade size during working memory maintenance.