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Design of a Virtual Reality Based Adaptive Response Technology for Children With Autism

机译:基于虚拟现实的自闭症儿童自适应反应技术设计

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Children with autism spectrum disorder (ASD) demonstrate potent impairments in social communication skills including atypical viewing patterns during social interactions. Recently, several assistive technologies, particularly virtual reality (VR), have been investigated to address specific social deficits in this population. Some studies have coupled eye-gaze monitoring mechanisms to design intervention strategies. However, presently available systems are designed to primarily chain learning via aspects of one's performance only which affords restricted range of individualization. The presented work seeks to bridge this gap by developing a novel VR-based interactive system with Gaze-sensitive adaptive response technology that can seamlessly integrate VR-based tasks with eye-tracking techniques to intelligently facilitate engagement in tasks relevant to advancing social communication skills. Specifically, such a system is capable of objectively identifying and quantifying one's engagement level by measuring real-time viewing patterns, subtle changes in eye physiological responses, as well as performance metrics in order to adaptively respond in an individualized manner to foster improved social communication skills among the participants. The developed system was tested through a usability study with eight adolescents with ASD. The results indicate the potential of the system to promote improved social task performance along with socially-appropriate mechanisms during VR-based social conversation tasks.
机译:自闭症谱系障碍(ASD)的儿童在社交互动过程中表现出强大的社交沟通能力受损,包括非典型的观看方式。最近,已经研究了几种辅助技术,特别是虚拟现实(VR),以解决该人群中的特定社会缺陷。一些研究将注视监视机制与干预策略设计结合在一起。然而,当前可用的系统被设计为主要仅通过一个人的表现方面来链接学习,这提供了有限的个性化范围。提出的工作试图通过开发一种新颖的基于VR的交互式系统以及Gaze敏感的自适应响应技术来弥合这一差距,该系统可以将基于VR的任务与眼动追踪技术无缝集成,从而智能地促进参与与提高社交沟通技能相关的任务。特别地,这样的系统能够通过测量实时观看模式,眼睛生理反应的细微变化以及性能指标来客观地识别和量化一个人的参与水平,从而以个性化的方式进行自适应反应,从而提高社交沟通能力在参与者之间。通过对八名ASD青少年的可用性研究对开发的系统进行了测试。结果表明,在基于VR的社交对话任务中,该系统具有促进改进社交任务性能以及社交适用机制的潜力。

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