Search Results (2,062)

AI travel assistants are increasingly designating hotels as “eco”, yet when the evidence is not independently verifiable, these recommendations may serve as persuasive cues or credible decision support. We present a preregistered 2 × 2 between-subject laboratory experiment (n = 63) that manipulates autonomy framing (Recommend vs. Plan) and evidence verifiability (verifiable vs. non-verifiable) in a realistic hotel-booking workflow with a standardized “Verify eco-claim” drawer. Phasic arousal was recorded at recommendation onset (E1) and verification initiation (E3), employing eye-tracking indexed verification behavior (verify clicks, time-to-verify, verification depth) and event-locked galvanic skin response (GSR). Verifiability did not directly speed up or deepen verification (H1 not supported), but verification was common (74.6% clicked Verify). Rather, autonomy influenced checking: Plan slowed verification and altered verification depth. E1 SCR revealed an Evidence × Autonomy interaction, which is consistent with an autonomy-boundary account (H4), rather than credibility stress emerging as a simple evidence main effect at E1 (H2 not supported as stated). Verification served as a repair moment: depending on the availability of diagnostic cues, arousal dynamics from E1 to E3 supported differential “repair” (H3). SCR dynamics explained incremental variance in perceived manipulation/greenwashing concern beyond condition and eye-tracking indices (H5b supported), but verification depth did not mediate effects on trust or delegation (H5a not supported). Overall, users’ interpretation of AI sustainability advice is influenced by autonomy, and multimodal process measures offer useful signals for auditing eco-recommendation designs in travel platforms. Full article

Background: Accurate evaluation of the Near Point of Convergence (NPC) is essential for diagnosing and managing convergence insufficiency (CI). Conventional assessment relies on the patient’s verbal feedback and the examiner’s visual observation, making it subjective and examiner-dependent. The AI-based MobileS platform, previously validated for both diagnosis and home-based therapy of CI, enables smartphone-based measurement and visualisation of NPC through eye tracking, without the need for verbal responses or additional equipment. This study, the third stage of our research programme, examined how ophthalmologists interpret NPC data when presented as videos versus AI-derived graphs. Methods: Twenty-two ophthalmologists completed an online questionnaire with 20 NPC test cases from the validated MobileS database, presented as both silent videos and AI-derived graphs. Accuracy was analysed using mixed-effects logistic regression, and continuous error was assessed using clustered bootstrap. Results: Graph-based interpretation showed higher odds of accurate NPC identification than video-based interpretation at the primary ±5 mm threshold (OR = 19.7, 95% CI: 13.50–28.74; p < 0.0001). Absolute error was lower for graphs than videos (Graphs − Videos: −22.73 mm; 95% CI: −26.88 to −18.59; p < 0.0001). “Uncertain” responses occurred in 28.2% of video-based assessments and 0% of graph-based assessments. Off-target errors decreased from 50.2% (videos) to 3.6% (graphs). Conclusions: AI-derived graphs of eye-movement data were associated with improved NPC estimation, suggesting a potential role in supporting clinical and tele-ophthalmology workflows. Full article

Background/Objectives: Hemodynamic monitoring is essential for guiding appropriate treatment by assessing cardiac output and volume status, as well as for preventing complications associated with excessive fluid administration. The EdgeFlow CW10 Plus is a device that extends conventional hemodynamic monitoring by incorporating pulmonary abnormality surveillance through B-line detection. This study aimed to evaluate whether the hemodynamic monitoring and pulmonary monitoring functions are well integrated, and verify the usability and efficiency of the system. Methods: A usability test was conducted with a panel of 15 medical professionals from diverse specialties and varying levels of clinical experience. Data from satisfaction surveys, heat maps, the System Usability Scale (SUS), and the NASA-TLX were analyzed to determine whether usability differences existed based on the duration of clinical experience. Results: The device demonstrated a high overall task success rate, averaging 93.2%. Regarding eye-tracking analysis based on clinical experience, it was observed that participants with more years of experience either failed to direct their gaze toward task-relevant user interface (UI) elements as effectively as those with fewer years of experience or showed similar patterns. Conclusions: The usability evaluation confirmed that the hemodynamic and pulmonary monitoring functions of the EdgeFlow CW 10 PLUS are well integrated, with the device demonstrating high usability and satisfaction. This integration is expected to support medical professionals in monitoring cardiac output and fluid status, facilitating timely therapeutic interventions while preventing complications related to fluid overload. Full article

Background: Eye-tracking (ET) devices are gaining attention in technology-based paediatric rehabilitation through their intrinsic ability to assess patients’ engagement and visual attention within motivating, technology-based environments. We conducted a systematic review of available evidence from 2004 to 2025 on the implementation of ET in rehabilitative trainings targeting paediatric populations with neurological and neurodevelopmental disorders. This paper aims to outline the rehabilitative outcomes pursued in the clinical populations considered. Methods: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Three electronic databases (PubMed, Web of Science, and Scopus) were consulted to summarise the state of the art of the last 20 years. Selected articles were categorised according to the type of treated disorder and the rehabilitated function. Results: ET devices have been increasingly integrated into paediatric rehabilitation with promising results across multiple neurodevelopmental conditions (e.g., ASD, ADHD, cerebral palsy). These systems have proven effective not only in training gaze control, but also in enhancing executive functions, social cognition, communication, and participation. Furthermore, they promote personalised and data-driven solutions and support high levels of engagement, feasibility, and user satisfaction. Conclusions: ET represents a promising frontier for paediatric rehabilitation, addressing various neurodevelopmental disorders. The gaze-contingent protocols employed have demonstrated potential effects in promoting adaptive behaviour across multiple developmental areas. Further research is warranted to provide shared guidance and to strengthen practice recommendations. Full article

The sustainable renewal of old residential communities faces increasing challenges in addressing the diverse environmental needs of older residents while respecting spatial constraints. Conventional approaches often treat older adults as a homogeneous group, overlooking how functional and social heterogeneity shape spatial perception. To address this gap, this study examines perceptual priorities in micro-public spaces of old residential communities in Qingdao, China, by classifying 60 community-dwelling older adults into four profiles using the Successful Aging framework. Participants performed free-viewing tasks using eye-tracking to observe 18 areas of interest (AOIs). Results reveal a clear perceptual hierarchy structured by individual profiles. Older adults with lower functional ability (Q3, Q4) allocate significant visual resources to safety-critical elements as a form of compensatory monitoring. Conversely, a systematic perceptual shift from survival-oriented assessment to quality-oriented evaluation was observed as functional and participatory reserves increased. High-participation groups (Q1, Q3) prioritized comfort facilities, while esthetic features attracted sustained attention primarily among the high-function/high-participation group (Q1). These findings provide empirical evidence for differentiated micro-renewal strategies that prioritize perceptual stress reduction and affordance enrichment in old residential communities. Full article

Eye movement research has emerged as a powerful tool in architectural and environmental design, offering insights into how people visually engage with built and natural surroundings. Eye tracking technology enables the study of visual attention, user engagement, and navigation patterns, thereby informing user-centered design. This paper reviews a wide and vast body of research that demonstrates eye tracking’s capacity to inform architectural and environmental design decisions by providing objective, data-driven insights into human perception and interaction with the built world. Key methodologies are discussed, including desktop, mobile, and VR-based systems, as well as recent advances in software analytics and artificial intelligence. Beyond summarizing the existing literature, this review critically evaluates methodological approaches, identifies key challenges, and outlines future research directions. The key findings indicate increased integration of immersive technologies, diversification of analytical paradigms, and expanded application in sustainable and user-centered design. However, methodological heterogeneity, limited ecological validation, and insufficient integration with design optimization frameworks remain significant limitations. This review provides a structured foundation for advancing interdisciplinary research and enhancing evidence-based architectural design. The paper concludes by outlining a forward-looking research agenda for creating more responsive, intuitive, and human-centered environments. Full article

This study evaluates how different alert conditions influence driver attention transitions under conditions of visual distraction using sequence analysis. Employing a within-subject experimental design, 13 participants underwent trials in a driving simulator, experiencing three distinct alert conditions: face-tracking auditory alerts, steering wheel auditory torque alerts, and a control scenario without alerts. An eye-tracking system was used to capture drivers’ gaze durations and sequences across three key areas of interest: road, dashboard, and tablet-based infotainment system. Analysis involved computation of transition probabilities, Markov chain modeling for long-term attentional distributions, and entropy analyses to quantify the randomness of gaze transitions. Results showed that face-tracking alerts significantly increased the likelihood of gaze redirection to the road compared to the other conditions, enhancing both immediate and sustained attention. Steering wheel torque alerts demonstrated minimal effectiveness, sometimes performing worse than the no-alert condition due to their passive nature, allowing drivers to bypass attention redirection. Steady-state analyses confirmed that face alerts notably improved sustained driver focus on the road by approximately 3.6%, reinforcing their utility for prolonged attentional control. Entropy analyses further revealed that face alerts provided an optimal balance between structured attention shifts and behavioral flexibility, enhancing attentional predictability. Findings are consistent with previous literature, emphasizing the superior effectiveness of active, gaze-based interventions over passive mechanisms. This research underscores the importance of designing proactive alert systems in vehicle safety technology to effectively mitigate visual distraction-related risks. Full article

Cognitive Learning Analytics (CLA) is an interdisciplinary domain that combines cognitive science and learning analytics to interpret and enhance human learning through theoretically grounded data analysis. It integrates learning analytics with models of cognition to support theoretically grounded interpretation of learner data. Learning analytics, since its inception in 2011, has developed as a research field and applied practice, focusing on “the measurement, collection, analysis, and reporting of data about learners and their contexts.” It focuses on understanding and optimizing learning processes and environments by leveraging large-scale, multimodal educational data. Cognitive science, in parallel, provides established theories of human learning, memory, attention, and metacognition. CLA links observable behaviors with theoretically defined cognitive mechanisms. Through the integration of cognitive theories and computational techniques, CLA models how learners process information, make decisions, and construct knowledge in digital learning environments. CLA employs diverse data sources—including clickstream logs, eye tracking, biometric signals, and linguistic traces—to infer learners’ cognitive and affective states. These inferences inform adaptive learning systems, personalized feedback mechanisms, and intelligent tutoring tools that respond dynamically to the learner’s mental workload, engagement, or metacognitive strategies. Full article

To ensure the security of mobile payments, anti-fraud warning messages serve as a critical defensive interface between users and potential risks. The effectiveness of their design directly influences users’ risk perceptions and security-related behaviors. The present study employed eye-tracking technology to examine the effectiveness of warning messages in mobile payment transfer scenarios and the impact of specific warning design features on user decision-making. Experiment 1 utilized a 2 (warning message: present vs. absent) × 3 (potential risk level: high, medium, low) within-subject design to test the fundamental role of warning message presence. Results indicated that the presence of warning messages significantly prolonged participants’ reaction times when selecting the transfer option, suggesting a more cautious decision-making process. Building on Experiment 1, Experiment 2 employed a 2 (warning color: red vs. blue) × 2 (warning semantic type: imperative vs. reminder) × 3 (potential risk level: high, medium, low) within-subject design and incorporated eye-tracking technology to investigate the effects of these design variables and underlying attentional mechanisms. Red warnings and imperative semantics were both found to significantly increase the likelihood of transfer rejection, with these design advantages being particularly pronounced in high-risk contexts. These findings provide empirical evidence to guide mobile payment platforms in optimizing dynamically adaptive, context-sensitive anti-fraud warning designs. Full article

Background: Strabismus diagnosis via the Alternate Cover Test (ACT) lacks quantitative standardization. This study proposes an AI-assisted framework using eye-tracking and machine learning for objective screening. Methods: Gaze coordinates were captured using a 60 Hz infrared eye tracker during ACT. Of the 291 initially screened individuals considered, 50 participants were ultimately included after quality filtering, yielding 335 valid samples. Seven algorithms were evaluated, with the dataset split into 294 training and 41 testing samples. Performance was measured by accuracy, sensitivity, specificity, PPV, and NPV. Results: Random Forest showed the best performance, achieving 97.56% accuracy (40/41) on the test set. It demonstrated a sensitivity of 1.00, specificity of 0.95, PPV of 0.95, and NPV of 1.00. The confusion matrix confirmed minimal false negatives, ensuring reliable clinical screening. Conclusions: The proposed system provides a robust, objective tool for strabismus diagnosis, standardizing ACT interpretation and reducing clinical bias. Full article

Student gaze behavior has been scarcely studied in real Latin American primary school classrooms. The objective of this study is to analyze the relationship between primary students’ eye behavior and cognitive development in urban and rural contexts. A quantitative method was employed, including 126 primary school students aged 6 to 8 years old, from urban and rural schools in Chile. Raven’s Colored Progressive Matrices (CPM) measured cognitive development, and students’ eye behavior was recorded during a real class using eye-tracking glasses. Eye behavior was analyzed in six areas of interest: (1) Own material (2) teacher, (3) teacher’s material, (4) peer, (5) peer’s material, and (6) non-interactional gaze. The results indicate that the CPM scale demonstrates adequate reliability (α = 0.89). In addition, no significant differences, nor relationship between eye behavior and cognitive development, were found by sex; however, significant differences were found by environment (urban versus rural). The regression analysis is significant (F(7, 102) = 6.173, p < 0.001) and suggests that gazing at the teacher’s material and one’s own material are negative predictors of non-interactional gaze or students’ disconnection from the class. In conclusion, distraction in the classroom is influenced by learning-related contextual variables rather than sex or cognitive development. Full article

Remote tower (rTWR) operations are reshaping air traffic control but introduce significant human-factor risks, notably cognitive fatigue induced by prolonged screen-based visual surveillance. To mitigate these risks in a safety-critical domain where missed detections can be catastrophic, we propose a non-intrusive, multimodal fatigue detection framework fusing ocular and cardiac signals. A high-fidelity simulation study with 36 controllers was conducted to collect eye-tracking and electrocardiogram (ECG) data, from which a 12-dimensional feature vector—integrating gaze entropy and heart rate variability (HRV)—was extracted. Addressing the severe class imbalance and scarcity of fatigue samples in physiological data, we developed a cost-sensitive XGBoost classifier combining SMOTE oversampling with a dynamically weighted loss function. Experimental results show that the proposed framework performed well under mixed-subject evaluation and improved sensitivity to fatigue events. Although a marked performance drop was observed under LOSO evaluation, personalized calibration partially alleviated this limitation, indicating the potential of the framework for real-time fatigue monitoring in remote tower operations. Full article

Background: Anorexia nervosa (AN) is a severe psychiatric disorder marked by restrictive eating, distorted body image, and high relapse rates. While cognitive-behavioral therapy (CBT) is a widely used treatment, its mechanisms of action in AN remain incompletely understood, particularly beyond self-reported symptom change. This study investigated the effects of a 12-week CBT intervention on both clinical and multimodal laboratory-based outcomes in women with restrictive-type AN. Methods: In a two-arm, pre–post randomized controlled trial (ClinicalTrials.gov: NCT07037017), 59 women with restrictive-type AN were randomized to a CBT intervention (n = 30) or no-treatment control (n = 29). A total of 50 participants (CBT: 26; control: 24) completed baseline and post-intervention assessments and were included in analyses. Outcomes included psychometric measures (eating disorder symptoms, depression, anxiety, body image-related obsessive–compulsive symptoms, and cognitive emotion regulation) and laboratory-based indices: electroencephalography (EEG), galvanic skin response (GSR), and eye-tracking during exposure to food- and body-related stimuli. Group × Time effects were analyzed using repeated-measures mixed-effects models, and statistical analyses were conducted using SPSS (Version 31; IBM Corp., Armonk, NY, USA). Results: Significant Group × Time interactions indicated greater improvements in the CBT group across all psychometric outcomes, including reduced eating disorder symptom severity (p < 0.001, η_p² = 0.28) and increased adaptive emotion regulation. CBT participants also showed significant reductions in EEG P300 and late positive potential (LPP) amplitudes to body-related stimuli, increased frontal alpha asymmetry, decreased visual fixation on salient body and food cues, and attenuated GSR reactivity (all p < 0.05). Exploratory correlations revealed that symptom improvements were associated with reductions in neurophysiological and attentional reactivity. Conclusions: To our knowledge, this is the first RCT in AN to demonstrate that CBT not only improves self-reported outcomes but also modulates neurophysiological and attentional processes implicated in the maintenance of the disorder. Multimodal laboratory assessments provided mechanistic insight into treatment effects and may inform personalized intervention strategies. CBT appears to facilitate recovery through both cognitive–emotional and physiological recalibration. Full article

Eye-tracking methodology represents a young but rapidly growing approach in tourism research, offering a direct window into the cognitive processes driving tourism stakeholders’ behaviour. However, a critical gap remains between the rapid adoption of this tool and the methodological rigour required to interpret its neurophysiological data. This critical review synthesizes 23 empirical studies (2020–2025) from the destination marketing and branding domain to diagnose eye-tracking’s state-of-the-art application. Adopting the SALSA framework (Search, Appraisal, Synthesis, Analysis) augmented by PRISMA 2020 guidelines, this study systematically searched Web of Science and Scopus databases. Studies were appraised using an eight-dimensional quality rubric, assessing from theoretical grounding to experimental design to statistical rigour. Findings revealed a “tool-first” exploratory phenomenon, where the majority of studies relied on basic fixation metrics to infer complex psychological states such as “interest”, when they could imply other cognitive states. Furthermore, most reviewed studies failed to control for stimulus-level confounds (e.g., luminance, AOI size) and utilized inappropriate data-handling procedures and methods, such as the absence of data cleaning and treating count and binary data as continuous data. These, coupled with transparency deficits, undermined the validity of their conclusions. Hence, a Checklist for Eye-Tracking Rigour (CETR) and a methodological decision tree were developed to guide researchers towards confirmatory and neurobiologically grounded research. Findings also provided a framework for managers/practitioners to more accurately interpret eye-tracking studies. Full article

Visual information should be presented clearly and effectively so that it is quickly and easily understood. The same principle applies to different types of maps and plans. This study explores the relationship between a map’s design and how users interact with it when searching for specific targets. Focusing on a digital tourist city map, we employed an eye-tracking technology to investigate how different cartographic designs (pictorial-based versus typography-based) influence visual search. As the need for visually appealing designs becomes an important part of the user experience, we further explored the observers’ perceptions of the maps’ visual appeal. The results show that the typography-based maps enabled a more effective visual search than the pictorial, as measured by search time, fixation count, and the number of fixations before locating the target. A greater amount of visual attention was directed towards the typography-based maps, as measured by completion time and several eye-tracking metrics during the observers’ evaluation of the maps’ visual appeal. Based on the results, this study highlights the practical implications of effective map design in enhancing users’ navigation and their visual engagement with cartographic data. Full article