Although it has often been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorder (ASD), relatively few investigations have indexed the impact of intervention and feedback approaches. This pilot study investigated the application of a novel robotic interaction system capable of administering and adjusting joint attention prompts to a small group (n = 6) of children with ASD. Across a series of four sessions, children improved in their ability to orient to prompts administered by the robotic system and continued to display strong attention toward the humanoid robot over time. The results highlight both potential benefits of robotic systems for directed intervention approaches as well as potent limitations of existing humanoid robotic platforms.

Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e., accuracy, confidence ratings, response latency, and stimulus discrimination) as well as how participants used their gaze to process facial information using an eye tracker. Participants in both groups were similarly accurate at basic facial affect recognition at varied levels of intensity. Despite similar performance characteristics, ASD participants endorsed lower confidence in their responses and substantial variation in gaze patterns in absence of perceptual discrimination deficits. These results add support to the hypothesis that deficits in emotion and face recognition for individuals with ASD are related to fundamental differences in information processing. We discuss implications of this finding in a VR environment with regards to potential future applications and paradigms targeting not just enhanced performance, but enhanced social information processing within intelligent systems capable of adaptation to individual processing differences.

Autism spectrum disorder (ASD) impacts 1 in 68 children in the US, with tremendous individual and societal costs. Technology-aided intervention, more specifically robotic intervention, has gained momentum in recent years due to the inherent affinity of many children with ASD towards technology. In this paper we present a novel robot-mediated intervention system for imitation skill learning, which is considered a core deficit area for children with ASD. The Robot-mediated Imitation Skill Training Architecture (RISTA) is designed in such a manner that it can operate either completely autonomously or in coordination with a human therapist depending on the intervention need. Experimental results are presented from small user studies validating system functionality, assessing user tolerance, and documenting subject performance. Preliminary results show that this novel robotic system draws more attention from the children with ASD and teaches gestures more effectively as compared to a human therapist. While no broad generalized conclusions can be made about the effectiveness of RISTA based on our small user studies, initial results are encouraging and justify further exploration in the future.

Autism Spectrum Disorders (ASD) are characterized by atypical patterns of behaviors and impairments in social communication. Among the fundamental social impairments in the ASD population are challenges in appropriately recognizing and responding to facial expressions. Traditional intervention approaches often require intensive support and well-trained therapists to address core deficits, with many with ASD having tremendous difficulty accessing such care due to lack of available trained therapists as well as intervention costs. As a result, emerging technology such as virtual reality (VR) has the potential to offer useful technology-enabled intervention systems. In this paper, an innovative VR-based facial emotional expression presentation system was developed that allows monitoring of eye gaze and physiological signals related to emotion identification to explore new efficient therapeutic paradigms. A usability study of this new system involving ten adolescents with ASD and ten typically developing adolescents as a control group was performed. The eye tracking and physiological data were analyzed to determine intragroup and intergroup variations of gaze and physiological patterns. Performance data, eye tracking indices and physiological features indicated that there were differences in the way adolescents with ASD process and recognize emotional faces compared to their typically developing peers. These results will be used in the future for an online adaptive VR-based multimodal social interaction system to improve emotion recognition abilities of individuals with ASD.

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and feedback. The system was designed to incorporate both a humanoid robot and a human examiner. We compared child performance within system across these conditions in a sample of preschool children with ASD (n=8) and a control sample of typically developing children (n=8). The system was well-tolerated in the sample, children with ASD exhibited greater attention to the robotic system than the human administrator, and for children with ASD imitation performance appeared superior during the robotic interaction.

Research indicates that human-robot interaction can help children with Autism Spectrum Disorder (ASD). While most early robot-mediated interaction studies were based on free interactions, recent studies have shown that robot-mediated interventions that focus on the core impairments of ASD such as joint attention deficit tend to produce better outcomes. Joint attention impairment is one of the core deficits in ASD that has an important impact in the neuropsychological development of these children. In this work, we propose a novel joint attention intervention system for children with ASD that overcomes several existing limitations in this domain such as the need to use body-worn sensors, non-autonomous robot operation requiring human involvement and lack of a formal model for robot-mediated joint attention interaction. We present a fully autonomous robotic system, called NORRIS, that can infer attention through a distributed non-contact gaze inference mechanism with an embedded Least-to-Most (LTM) robot-mediated interaction model to address the current limitations. The system was tested in a multi-session user study with 14 young children with ASD. The results showed that participants’ joint attention skills improved significantly, their interest in the robot remained consistent throughout the sessions, and the LTM interaction model was effective in promoting the children’s performance.

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment.

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