Abstract
Responding to one's name is among the earliest-emerging social orienting behaviors and is one of the most prominent aspects in the detection of Autism Spectrum Disorder (ASD). Typically developing children exhibit near-reflexive orienting to their name, whereas children with ASD often demonstrate reduced frequency, increased latency, or atypical patterns of response. In this study, we examine differential responsiveness to quantify name-calling stimuli delivered by both human agents and NAO, a humanoid robot widely employed in socially assistive interventions for autism. The analysis focuses on multiple behavioral parameters, including eye contact, response latency, head and facial orientation shifts, and duration of sustained interest. Video-based computational methods were employed, incorporating face detection, eye region tracking, and spatio-temporal facial analysis, to obtain fine-grained measures of children's responses. By comparing neurotypical and neuroatypical groups under controlled human-robot conditions, this work aims to understand how the source and modality of social cues affect attentional dynamics in name-calling contexts. The findings advance both the theoretical understanding of social orienting deficits in autism and the applied development of robot-assisted assessment tools.
Abstract (translated)
对名字的反应是最早出现的社会定向行为之一，也是检测自闭症谱系障碍（ASD）最突出的方面之一。典型发育儿童对名字会表现出近乎反射性的定向反应，而自闭症儿童则常出现反应频率降低、潜伏期延长或反应模式异常。本研究通过量化人类实验者与广泛用于自闭症社会辅助干预的NAO人形机器人发出的呼叫名字刺激，分析不同主体的差异反应。研究聚焦多项行为参数，包括眼神接触、反应潜伏期、头部与面部转向角度以及持续关注时长。采用基于视频的计算方法，整合人脸检测、眼部区域追踪及时空面部分析，以获取儿童反应的精细测量。通过对比神经典型与神经非典型群体在受控人机交互条件下的表现，本研究旨在理解社会线索的来源与模态如何影响呼叫名字情境中的注意力动态。研究结果既推进了对自闭症社会定向缺陷的理论理解，也促进了机器人辅助评估工具的实践发展。
URL
https://arxiv.org/abs/2603.22759
