关键词: 视觉搜索, 孤独症谱系障碍, 眼动, 机器学习

Abstract: Objective To describe the eye movement pattern during visual search process,so as to explore whether visual search patterns could be potentially useful to identify children with autism spectrum disorders (ASD). Methods Totally 15 ASD children and 17 typically developing (TD) children matched with intelligence quotient (IQ),gender and chronological age were enrolled in this study from March to July 2017,and their eye-movement data when performing visual search task were recorded.The machine learning method was used to establish a model discriminating ASD from TD,including the fixations,fixation duration and fixation path during the visual search task.The performance of the classification model was assessed by the accuracy,sensitivity and specificity of classifying ASD. Results 1)ASD children showed shorter reaction time in visual search task compared to TD in the condition of target-off(F=3.76,P<0.05).2) By using eye movement patterns,ASD children could be discriminated from TD children accurately,with the classification accuracy of 78.13%,specificity of 70.59% and sensitivity of 86.67%.3) The score of the discriminative features was negatively related to scores of the Childhood Autism Rating Scale (r=-0.497,P=0.030). Conclusion The visual search pattern detected by eye movement could be potentially useful to identify children with ASD.

Key words: visual search, autism spectrum disorders, eye-movement, machine learning