Computer Vision Analysis Captures Atypical Attention in Toddlers with Autism

Autor/inn/en	Campbell, Kathleen; Carpenter, Kimberly L. H.; Hashemi, Jordan; Espinosa, Steven; Marsan, Samuel; Borg, Jana Schaich; Chang, Zhuoqing; Qiu, Qiang; Vermeer, Saritha; Adler, Elizabeth; Tepper, Mariano; Egger, Helen L.; Baker, Jeffery P.; Sapiro, Guillermo; Dawson, Geraldine
Titel	Computer Vision Analysis Captures Atypical Attention in Toddlers with Autism
Quelle	In: Autism: The International Journal of Research and Practice, 23 (2019) 3, S.619-628 (10 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Campbell, Kathleen) ORCID (Hashemi, Jordan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1362-3613
DOI	10.1177/1362361318766247
Schlagwörter	Autism; Pervasive Developmental Disorders; Toddlers; Video Technology; Motion; Attention; Responses; Child Behavior; Age Differences; At Risk Persons; Social Behavior; Visual Stimuli; Naming; Parents; Prompting; Diagnostic Tests; Observation; Autism Diagnostic Observation Schedule + Suchen Sie Ihr Suchwort? Autismus; Infant; Infants; Toddler; Kleinkind; Bewegungsablauf; Aufmerksamkeit; Age; Difference; Age difference; Altersunterschied; Risikogruppe; Social behaviour; Soziales Verhalten; Eltern; Benutzerführung; Diagnostic test; Diagnostischer Test; Beobachtung
Abstract	To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundred and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. Computer vision analysis measured participants' attention and orienting in response to name calls. Reliability of the computer vision analysis algorithm was tested against a human rater. Differences in behavior were analyzed between the autism spectrum disorder group and the comparison group. Reliability between computer vision analysis and human coding for orienting to name was excellent (intra-class coefficient 0.84, 95% confidence interval 0.67-0.91). Only 8% of toddlers with autism spectrum disorder 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 autism spectrum disorder (2.02 vs 1.06 s, p = 0.04). Sensitivity for autism spectrum disorder of atypical orienting was 96% and specificity was 38%. Older toddlers with autism spectrum disorder 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 autism spectrum disorder. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01