New Eye Tracking Metrics System: The Value in Early Diagnosis of Autism Spectrum Disorder

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). These metrics were 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 was assessed using linear regression. Sensitivity and specificity of the cut-off scores were also evaluated 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. There were no significant differences in total fixation time or pupil size (p > 0.05). Additionally, FAS was negatively correlated with ADOS-2 total scores and the social affect (SA) subscale (p < 0.05). Among these new ET metrics, AVC yielded the best sensitivity (88-100%) and specificity (80-88%) with a cut-off score of 0.305-0.306, followed by FAS and ASC for distinguishing 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.