Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder.
Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder.
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DOI：
10.1038/s41598-018-35215-8
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发表时间：
2018-11-19
影响因子：
4.6
通讯作者：
Sapiro G
中科院分区：
文献类型：
--
作者：
Dawson G;Campbell K;Hashemi J;Lippmann SJ;Smith V;Carpenter K;Egger H;Espinosa S;Vermeer S;Baker J;Sapiro G
有证据表明，运动功能的差异是自闭症谱系障碍（ASD）的早期特征。在儿童时期发展的运动能力的一个方面是姿势控制，反映在保持稳定的头部和身体位置而不过度摇摆的能力上。观察性研究记录了年龄较大的ASD儿童在姿势控制方面的差异。本研究使用计算机视觉分析来评估中线头部姿势控制，反映在104名年龄在16-31个月（平均= 22个月）之间的幼儿在主动注意状态下的自发头部运动率中，其中22人被诊断为ASD。时间序列数据显示，当蹒跚学步的孩子观看描绘社会和非社会刺激的电影时，头部运动的速度存在很大的组间差异。与非ASD幼儿相比，患有ASD的幼儿表现出显着更高的头部运动速率，这表明在保持头部中线位置的同时参与注意力系统的困难。使用数字表型分析方法（如计算机视觉分析）来量化早期运动行为的变化将允许更精确，客观和定量表征早期运动特征，并可能为早期自闭症风险识别提供新的自动化方法。
Evidence suggests that differences in motor function are an early feature of autism spectrum disorder (ASD). One aspect of motor ability that develops during childhood is postural control, reflected in the ability to maintain a steady head and body position without excessive sway. Observational studies have documented differences in postural control in older children with ASD. The present study used computer vision analysis to assess midline head postural control, as reflected in the rate of spontaneous head movements during states of active attention, in 104 toddlers between 16–31 months of age (Mean = 22 months), 22 of whom were diagnosed with ASD. Time-series data revealed robust group differences in the rate of head movements while the toddlers watched movies depicting social and nonsocial stimuli. Toddlers with ASD exhibited a significantly higher rate of head movement as compared to non-ASD toddlers, suggesting difficulties in maintaining midline position of the head while engaging attentional systems. The use of digital phenotyping approaches, such as computer vision analysis, to quantify variation in early motor behaviors will allow for more precise, objective, and quantitative characterization of early motor signatures and potentially provide new automated methods for early autism risk identification.
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影响因子：
3.9
作者：
Gotham, Katherine;Risi, Susan;Lord, Catherine
通讯作者：
Lord, Catherine
DOI：
10.1177/1362361318766247
发表时间：
2019-04
期刊：
Autism : the international journal of research and practice
影响因子：
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作者：
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影响因子：
1.7
作者：
Esposito, Gianluca;Venuti, Paola;Muratori, Filippo
通讯作者：
Muratori, Filippo
影响因子：
3.9
作者：
Lim, Yi Huey;Lee, Hoe C.;Morris, Susan L.
通讯作者：
Morris, Susan L.