Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.
Cognitive and Information Sciences, University of California, Merced, USA.
Autism Res. 2022 Feb;15(2):305-316. doi: 10.1002/aur.2646. Epub 2021 Nov 27.
The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty-three children with typical development (TD) were videotaped while engaged in a face-to-face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions. LAY SUMMARY: By implementing an objective behavioral quantifying technique, our study demonstrated that children with autism had more body movement during face-to-face conversation, and they moved in a less complex way. The current diagnosis of autism heavily relies on doctor's experiences. These findings suggest a potential that autism might be automatically screened during daily social interactions.
大多数现有的研究都是通过问卷调查和行为编码技术来调查自闭症谱系障碍（ASD）患者明显的社交行为特征。作为一项新颖的研究，本研究旨在量化社交互动过程中产生的复杂动作，以测试 ASD 运动动力学的差异及其在社交互动中的趋同或缺乏趋同。20 名 ASD 儿童和 23 名典型发育儿童（TD）与访谈者进行面对面交谈时被录像。使用图像差分技术提取运动时间序列。进行频谱分析以量化运动的平均功率和运动的分形标度。复杂性匹配度用于捕捉访谈者和儿童之间行为协调性的水平。结果表明，ASD 儿童的平均功率明显更高（p<0.01），分形标度更陡（p<0.05），这表明与 TD 同龄人相比，ASD 儿童的动作过度且复杂程度较低。儿童和访谈者之间存在复杂性匹配，但 ASD 和 TD 儿童之间的匹配强度没有可靠差异。访谈者行为的描述性趋势表明，她的动作适应了同时匹配 ASD 和 TD 动作。我们的研究结果可能为寻找 ASD 的新型行为标志物以及在日常社交互动中开发自动 ASD 筛查技术提供启示。
