Online Engagement Detection and Task Adaptation in a Virtual Reality Based Driving Simulator for Autism Intervention
作者： Dayi Bian , Joshua Wade , Zachary Warren , Nilanjan Sarkar
DOI: 10.1007/978-3-319-40238-3_51
关键词: Adaptation (computer science) 、 Affective computing 、 Autism 、 Driving simulator 、 Basic skills 、 Cognitive psychology 、 Virtual reality 、 Task (project management) 、 Human–computer interaction 、 Psychology 、 Autism spectrum disorder
摘要: Individuals with Autism spectrum disorder (ASD) have difficulty functioning independently on essential tasks that require adaptive skills such as driving. Recently, computer-aided technology, Virtual Reality (VR), is being widely used in ASD intervention to teach basic children autism. However, most of these works either do not use feedback or solely performance from the participant for system adaptation. This paper introduces a physiology-based task adaptation mechanism virtual environment driving skill training. The was autonomously adjusted based participant’s and engagement level provide an optimal challenge. detected using affective model which developed our previous experimental data therapist’s ratings. We believe this can be useful teaching adolescents ASD.
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