Superpower Glass: Delivering Unobtrusive Realtime Social Cues in Wearable Systems We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers realtime social cues to the wearer. We evaluate the system as a behavioral aid for children with Autism Spectrum Disorder (ASD), who can greatly benefit from realtime noninvasive emotional cues and are more sensitive to sensory input than neurotypically developing children. In addition, we present a mobile application that enables users of the wearable aid to review their videos along with autocurated emotional information on the video playback bar. This integrates our learning aid into the context of behavioral therapy. Expanding on our previous work describing inlab trials, this paper presents our system and applicationlevel design decisions in depth as well as the interface learnings gathered during the use of the system by multiple children with ASD in an athome iterative trial.

Requirements for Robotic Interpretation of Social Signals xe2x80x9cin the Wildxe2x80x9d: Insights from Diagnostic Criteria of Autism Spectrum Disorder The last few decades have seen widespread advances in technological means to characterise observable aspects of human behaviour such as gaze or posture. Among others, these developments have also led to significant advances in social robotics. At the same time, however, social robots are still largely evaluated in idealised or laboratory conditions, and it remains unclear whether the technological progress is sufficient to let such robots move xe2x80x9cinto the wildxe2x80x9d. In this paper, we characterise the problems that a social robot in the real world may face, and review the technological state of the art in terms of addressing these. We do this by considering what it would entail to automate the diagnosis of Autism Spectrum Disorder (ASD). Just as for social robotics, ASD diagnosis fundamentally requires the ability to characterise human behaviour from observable aspects. However, therapists provide clear criteria regarding what to look for. As such, ASD diagnosis is a situation that is both relevant to realworld social robotics and comes with clear metrics. Overall, we demonstrate that even with relatively clear therapistprovided criteria and current technological progress, the need to interpret covert behaviour cannot yet be fully addressed. Our discussions have clear implications for ASD diagnosis, but also for social robotics more generally. For ASD diagnosis, we provide a classification of criteria based on whether or not they depend on covert information and highlight presentday possibilities for supporting therapists in diagnosis through technological means. For social robotics, we highlight the fundamental role of covert behaviour, show that the current stateoftheart is unable to characterise this, and emphasise that future research should tackle this explicitly in realistic settings.