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神经发育障碍儿童中照顾者与儿童互动的计算机视觉分析:初步报告。

Computer Vision Analysis of Caregiver-Child Interactions in Children with Neurodevelopmental Disorders: A Preliminary Report.

作者信息

Isaev Dmitry Yu, Sabatos-DeVito Maura, Di Martino J Matias, Carpenter Kimberly, Aiello Rachel, Compton Scott, Davis Naomi, Franz Lauren, Sullivan Connor, Dawson Geraldine, Sapiro Guillermo

机构信息

Department of Biomedical Engineering, Duke University, Durham, NC, USA.

Duke Center for Autism and Brain Development, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.

出版信息

J Autism Dev Disord. 2024 Jun;54(6):2286-2297. doi: 10.1007/s10803-023-05973-0. Epub 2023 Apr 27.

Abstract

We report preliminary results of computer vision analysis of caregiver-child interactions during free play with children diagnosed with autism (N = 29, 41-91 months), attention-deficit/hyperactivity disorder (ADHD, N = 22, 48-100 months), or combined autism + ADHD (N = 20, 56-98 months), and neurotypical children (NT, N = 7, 55-95 months). We conducted micro-analytic analysis of 'reaching to a toy,' as a proxy for initiating or responding to a toy play bout. Dyadic analysis revealed two clusters of interaction patterns, which differed in frequency of 'reaching to a toy' and caregivers' contingent responding to the child's reach for a toy by also reaching for a toy. Children in dyads with higher caregiver responsiveness had less developed language, communication, and socialization skills. Clusters were not associated with diagnostic groups. These results hold promise for automated methods of characterizing caregiver responsiveness in dyadic interactions for assessment and outcome monitoring in clinical trials.

摘要

我们报告了对被诊断患有自闭症(N = 29,41 - 91个月)、注意力缺陷多动障碍(ADHD,N = 22,48 - 100个月)或自闭症合并ADHD(N = 20,56 - 98个月)的儿童以及神经典型儿童(NT,N = 7,55 - 95个月)在自由玩耍期间照顾者与儿童互动进行计算机视觉分析的初步结果。我们对“伸手拿玩具”进行了微观分析,以此作为发起或回应玩具玩耍回合的替代指标。二元分析揭示了两种互动模式集群,它们在“伸手拿玩具”的频率以及照顾者对孩子伸手拿玩具的 contingent 反应(即也伸手拿玩具)方面存在差异。照顾者反应性较高的二元组中的儿童语言、沟通和社交技能发展较差。集群与诊断组无关。这些结果为在二元互动中表征照顾者反应性的自动化方法在临床试验中的评估和结果监测方面带来了希望。

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