Department of Computer Science, University of Pisa, Largo Pontecorvo 3, 56127 Pisa, Italy.
Department of Child Psychiatry and Psychopharmacology, IRCCS Stella Maris Foundation, 56018 Pisa, Italy.
Sensors (Basel). 2021 Mar 11;21(6):1971. doi: 10.3390/s21061971.
Observing how children manipulate objects while they are playing can help detect possible autism spectrum disorders (ASD) at an early stage. For this purpose, specialists seek the so-called "red-flags" of motor signature of ASD for more precise diagnostic tests. However, a significant drawback to achieve this is that the observation of object manipulation by the child very often is not naturalistic, as it involves the physical presence of the specialist and is typically performed in hospitals. In this framework, we present a novel Internet of Things support in the form factory of a smart toy that can be used by specialists to perform indirect and non-invasive observations of the children in naturalistic conditions. While they play with the toy, children can be observed in their own environment and without the physical presence of the specialist. We also present the technical validation of the technology and the study protocol for the refinement of the diagnostic practice based on this technology.
观察儿童在玩耍时如何操作物体有助于在早期发现可能的自闭症谱系障碍 (ASD)。为此，专家寻求所谓的 ASD 运动特征的“红旗”，以进行更精确的诊断测试。然而，实现这一目标的一个显著缺点是，儿童对物体操作的观察通常不是自然的，因为它涉及专家的实际存在，并且通常在医院进行。在这个框架内，我们提出了一种新的物联网支持形式，即一个智能玩具工厂，可以由专家在自然条件下对儿童进行间接和非侵入性观察。当孩子们玩玩具时，可以在他们自己的环境中观察他们，而无需专家的实际存在。我们还介绍了该技术的技术验证以及基于该技术细化诊断实践的研究方案。
