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Recognition of Gestural Behaviors Expressed by Humanoid Robotic Platforms for Teaching Affect Recognition to Children with Autism-A Healthy Subjects Pilot Study

机译:类人机器人平台表达的手势行为的识别对自闭症儿童的情感识别教学-健康受试者的初步研究

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Autism Spectrum Disorder (ASD) is a neurodevelopmen-tal disorder that is characterized by impaired social interactions and restricted, repetitive behaviors. Children who are considered to be within the spectrum tend to lack the social interaction, facial processing, and emotion recognition and implementation skills that typically developing children possess. These impairments inhibit positive social interactions, relationship building, and effective communication, which could potentially lead to distress and frustration for the child. This study focuses on developing a system to teach five of the six universal emotions. Therefore, we created an emotional gesture set to be performed on a pair of humanoid robot platforms, the NAO and the Mini Darwin. As a step towards reaching that goal of teaching and assessing children with ASD, we conducted a pilot study with able-bodied adults to validate that the gesture set created was easily recognizable. In this pilot study, we asked 137 able-bodied adult participants to watch the system perform gestures that associated to emotions. Then, we asked them to identify the emotion that the system was attempting to portray. Gestures achieved recognition rates ranging in values, with a maximum rate of 96% for sadness and a minimum rate of 57% for happiness.
机译:自闭症谱系障碍(ASD)是一种神经发育障碍,其特征是社交互动障碍和受限的重复性行为。被认为属于这一范围的儿童往往缺乏通常发展中的儿童所具有的社交互动,面部处理以及情感识别和实施技能。这些障碍会阻碍积极的社会互动,建立关系和有效的沟通,从而可能导致孩子的困扰和沮丧。这项研究的重点是开发一种系统来教授六种普遍情绪中的五种。因此,我们创建了一个情感手势集,可以在一对人形机器人平台NAO和Mini Darwin上执行。为了实现教学和评估ASD儿童的目标,我们与身体健全的成年人进行了一项初步研究,以验证所创建的手势集易于识别。在这项初步研究中,我们要求137名身体健全的成人参与者观看系统执行与情感相关的手势。然后,我们要求他们确定系统试图描绘的情感。手势的识别率各不相同,悲伤的最高识别率为96%,幸福的最低识别率为57%。

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