Using Physiological Signals and Machine Learning Algorithms to Measure Attentiveness During Robot-Assisted Social Skills Intervention: A Case Study of Two Children with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) often face barriers in accessing opportunities across a range of educational, employment, and social contexts. One of these barriers is the development of effective communication skills sufficient for navigating the social demands of everyday environments. Fortunately, researchers have established evidence-based practices (EBP) for teaching critical communication skills to individuals with ASD [1]. One EBP that has received a great deal of attention over the last few decades is technology-aided instruction and intervention (TAII) [1], [2]. TAII is an instructional practice in which technology is an essential component and is used to facilitate behavior change. Further, it encompasses a wide range of applications including computer-assisted instruction, virtual and augmented reality, augmentative and alternative communication, and robot-assisted intervention [2].