Abstract
Despite the increment of researches related to Social Assistive Robotics (SAR), achieving a plausible Robot-Assisted Diagnosis (RAD) for Children with Autism Spectrum Disorders (CwASD) remains a considerable challenge to the clinical and robotics community. The work of specialists regarding ASD diagnosis is hard and labor-intensive due to the condition’s manifestations are inherently heterogeneous and makes the process more difficult. Besides, the aforementioned complexity may be the main reason for the slow progress in the development of SAR with diagnostic purposes. Thus, this work provides a comprehensive Robot-Assisted Intervention for CwASD showing the conditions in which a Robot-based approach can be useful to assess autism risk factors for an autism diagnosis purpose. The intervention scheme consists of an improved version of a multimodal environment for Robot-based intervention proposed in our previous work. More specifically, we compared the behavior of CwASD with that of children in a control group during a human/robot-mediated intervention while Joint Attention (JA) behaviors are elicited and analyzed. Through statistical data analysis, it was possible to identify that 17 out of 23 children of the CwASD group showed a different behavior pattern related to three characteristics of autism, which suggests that this pattern can be used to identify autism risk factors through Robot-based interventions.
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