Recent studies suggest that robot-based interventions are potentially effective in diagnosis and therapy of autism spectrum disorder (ASD), demonstrating that robots can improve the engagement abilities and attention in autistic children. While methodological approaches vary significantly in these studies and are not unified yet, researchers often develop similar solutions based on similar conceptual and practical premises. We systematically review the latest robot-intervention techniques in ASD research (18 research papers), comparing multiple dimensions of technological and experimental implementation. In particular, we focus on sensor-based assessment systems for automated and unbiased quantitative assessments of children’s engagement and attention fluctuations during interaction with robots. We examine related technologies, experimental and methodological setups, and the empirical investigations they support. We aim to assess the strengths and limitations of such approaches in a diagnostic context and to evaluate their potential in increasing our knowledge of autism and in supporting the development of social skills and attentional dispositions in ASD children. Using our acquired results from the overview, we propose a set of social cues and interaction techniques that can be thought to be most beneficial in robot-related autism intervention.

中文翻译：

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人形机器人和自闭症儿童：评估社会注意力和参与度的技术工具综述

最近的研究表明，基于机器人的干预措施在自闭症谱系障碍 (ASD) 的诊断和治疗中可能有效，这表明机器人可以提高自闭症儿童的参与能力和注意力。虽然这些研究中的方法学方法差异很大并且尚未统一，但研究人员经常基于相似的概念和实践前提开发类似的解决方案。我们系统地回顾了 ASD 研究中最新的机器人干预技术（18 篇研究论文），比较了技术和实验实施的多个维度。特别是，我们专注于基于传感器的评估系统，用于对儿童在与机器人交互过程中的参与度和注意力波动进行自动化和公正的定量评估。我们研究相关技术，实验和方法设置，以及它们支持的实证研究。我们的目标是评估这些方法在诊断背景下的优势和局限性，并评估它们在增加我们对自闭症的认识以及支持 ASD 儿童社交技能和注意力倾向发展方面的潜力。利用我们从概述中获得的结果，我们提出了一组社交线索和交互技术，这些技术可以被认为对机器人相关的自闭症干预最有益。