ArticleFrontiers in psychiatry2024
New eye tracking metrics system: the value in early diagnosis of autism spectrum disorder.
Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Diagnostic Potential of Eye Tracking to Detect Autism Spectrum Disorder in Children: A Systematic Review.Medical sciences (Basel, Switzerland) · 2026Pooled it
- Improving Autism Diagnosis Across Ages Using Eye-Tracking and Temporal Transformer Models.Sensors (Basel, Switzerland) · 2026Article
- Participant-Independent Classification of Autism-Related Visual Attention Patterns from Eye-Tracking Scanpath Images Using a Global-Local Fusion Network.Journal of eye movement research · 2026Article
- Early Detection Methods for Autism Spectrum Disorder: From Clinical Screening to Multimodal AI.Diagnostics (Basel, Switzerland) · 2026Review
- Graph Neural Networks and sequential architectures for autism detection from eye-tracking biomarkers: a multi-site study.BMC psychiatry · 2026Article
- Home-based eye tracking for early autism screening: a scoping review of approaches, evidence, and implementation challenges.BMC psychiatry · 2026Article
- Artificial-intelligence-based developmental screening for pre-school children (ages 3-6): a scoping review of deployed tools, clinical validity, equity, and implementation in guidance-center settings.Frontiers in psychology · 2026Review
- Eye-Tracking as a Screening Tool in the Early Diagnosis of Autism Spectrum Disorder: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2025Review
- Diagnosing autism spectrum disorder based on eye tracking technology using deep learning models.Frontiers in medicine · 2025Article
- Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
4 authors.
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Abstract
Background: Eye tracking (ET) is emerging as a promising early and objective screening method for autism spectrum disorders (ASD), but it requires more reliable metrics with enhanced sensitivity and specificity for clinical use. Methods: This study introduces a suite of novel ET metrics: Area of Interest (AOI) Switch Counts (ASC), Favorable AOI Shifts (FAS) along self-determined pathways, and AOI Vacancy Counts (AVC), applied to toddlers and preschoolers diagnosed with ASD. The correlation between these new ET metrics and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) scores via linear regression and sensitivity and specificity of the cut-off scores were assessed to predict diagnosis. Results: Our findings indicate significantly lower FAS and ASC and higher AVC (P<0.05) in children with ASD compared to their non-ASD counterparts within this high-risk cohort; the significance was not seen in total fixation time neither pupil size (p > 0.05). Furthermore, FAS was negatively correlated with ADOS-2 total scores and social affect (SA) subscale (p < 0.05). Among these new ET metrics, AVC yielded the best sensitivity 88-100% and specificity 80-88% with cut off score 0.305-0.306, followed by FAS and ASC to separate ASD from non-ASD for diagnosis. Conclusions: This study confirms the utility of innovative ET metrics-FAS, AVC, and ASC-which exhibit markedly improved sensitivity and specificity, enhancing ASD screening and diagnostic processes.
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