Applying Eye Tracking to Identify Autism Spectrum Disorder in Children

被引:88
|
作者
Wan, Guobin [1 ]
Kong, Xuejun [2 ]
Sun, Binbin [1 ]
Yu, Siyi [3 ]
Tu, Yiheng [3 ]
Park, Joel [3 ]
Lang, Courtney [3 ]
Koh, Madelyn [2 ]
Wei, Zhen [1 ]
Feng, Zhe [1 ]
Lin, Yan [1 ]
Kong, Jian [3 ]
机构
[1] Shenzhen Matern & Child Healthcare Hosp, 3012 Fuqiang Rd, Shenzhen 518040, Guangdong Sheng, Peoples R China
[2] Harvard Med Sch, Massachusetts Gen Hosp, Martinos Ctr, 149 13th St,1118A, Charlestown, MA 02129 USA
[3] Harvard Med Sch, Massachusetts Gen Hosp, Dept Psychiat, 120 2nd Ave,Room 101, Charlestown, MA 02129 USA
关键词
Autism; Eye tracking; Fixation time; Machine learning; Face; TODDLERS; ADULTS; LEVEL;
D O I
10.1007/s10803-018-3690-y
中图分类号
B844 [发展心理学(人类心理学)];
学科分类号
040202 ;
摘要
Eye tracking (ET) holds potential for the early detection of autism spectrum disorder (ASD). To overcome the difficulties of working with young children, developing a short and informative paradigm is crucial for ET. We investigated the fixation times of 37 ASD and 37 typically developing (TD) children ages 4-6 watching a 10-second video of a female speaking. ASD children showed significant reductions in fixation time at six areas of interest. Furthermore, discriminant analysis revealed fixation times at the mouth and body could significantly discriminate ASD from TD with a classification accuracy of 85.1%, sensitivity of 86.5%, and specificity of 83.8%. Our study suggests that a short video clip may provide enough information to distinguish ASD from TD children.
引用
收藏
页码:209 / 215
页数:7
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