Computer vision analysis captures atypical attention in toddlers with autism.

Computer vision analysis captures atypical attention in toddlers with autism.
复制标题

DOI:
10.1177/1362361318766247
复制
发表时间:
2019-04
期刊:
Autism : the international journal of research and practice
影响因子:
--
通讯作者:
Dawson G
Dawson G
中科院分区:
其他
文献类型:
--
作者:
Campbell K;Carpenter KL;Hashemi J;Espinosa S;Marsan S;Borg JS;Chang Z;Qiu Q;Vermeer S;Adler E;Tepper M;Egger HL;Baker JP;Sapiro G;Dawson G

文献摘要

参考文献

被引文献

相似文献

目的:探讨计算机视觉分析(CVA)对自闭症谱系障碍(ASD)幼儿非典型定向和注意行为的检测能力。104名16-31个月大的幼儿(平均22名)参与了这项研究。22名幼儿患有自闭症,82名有典型的发育迟缓或发育迟缓。蹒跚学步的孩子们在平板电脑上观看视频刺激,而内置的摄像头则记录他们的头部运动。CVA测量了参与者对辱骂的反应的注意力和方向。CVA算法的可靠性是针对人类评分者进行测试的。分析ASD组和对照组之间的行为差异。CVA和人类编码对名字定向的可靠性非常好(ICC为0.84,95%CI为0.67~0.91)。只有8%的患有自闭症的幼儿倾向于在1号试验中点名,而对照组的这一比例为63%(p=0.002)。患有自闭症的幼儿的平均定向潜伏期显著延长(2.02比1.06秒,p=0.04)。非典型定向法诊断ASD的敏感性为96%,特异性为38%。患有自闭症的年纪较大的幼儿对视频的整体注意力较少(p=0.03)。自动编码提供了一种可靠的、定量的方法来检测患有自闭症儿童的非典型社交定向和减少持续注意力。
To demonstrate the capability of computer vision analysis (CVA) to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder (ASD). 104 toddlers 16-31 months old (Mean=22) participated in this study. Twenty-two of the toddlers had ASD and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. CVA measured participants' attention and orienting in response to name calls. Reliability of the CVA algorithm was tested against a human rater. Differences in behavior were analyzed between the ASD group and the comparison group. Reliability between CVA and human coding for orienting to name was excellent (ICC 0.84, 95%CI 0.67-0.91). Only 8% of toddlers with ASD oriented to name calling on >1 trial, compared to 63% of toddlers in the comparison group (p=0.002). Mean latency to orient was significantly longer for toddlers with ASD (2.02 vs 1.06 sec, p=0.04). Sensitivity for ASD of atypical orienting was 96%, and specificity was 38%. Older toddlers with ASD showed less attention to the videos overall (p=0.03). Automated coding offers a reliable, quantitative method for detecting atypical social orienting and reduced sustained attention in toddlers with ASD.
自闭症诊断观察表: 提高诊断有效性的修订算法
DOI: 10.1007/s10803-006-0280-1
发表时间: 2007-04-01
影响因子: 3.9
作者:
Gotham, Katherine;Risi, Susan;Lord, Catherine
通讯作者: Lord, Catherine
DOI: 10.1016/j.jpeds.2017.01.021
发表时间: 2017-04-01
影响因子: 5.1
作者:
Campbell, Kathleen;Carpenter, Kimberly L. H.;Dawson, Geraldine
通讯作者: Dawson, Geraldine
DOI: 10.1111/cdev.12473
发表时间: 2016-03
期刊: Child development
影响因子: 4.6
作者:
Chawarska K;Ye S;Shic F;Chen L
通讯作者: Chen L
DOI: 10.1023/a:1005592401947
发表时间: 2000-06-01
影响因子: 3.9
作者:
Lord, C;Risi, S;Rutter, M
通讯作者: Rutter, M
DOI: 10.1016/j.rasd.2011.11.005
发表时间: 2012-04
影响因子: 2.5
作者:
Elison JT;Sasson NJ;Turner-Brown LM;Dichter G;Bodfish JW
通讯作者: Bodfish JW