It has been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders. This pilot feasibility study evaluated the application of a novel adaptive robot-mediated system capable of both administering and automatically adjusting joint attention prompts to a small group of preschool children with autism spectrum disorders (n = 6) and a control group (n = 6). Children in both groups spent more time looking at the humanoid robot and were able to achieve a high level of accuracy across trials. However, across groups, children required higher levels of prompting to successfully orient within robot-administered trials. The results highlight both the potential benefits of closed-loop adaptive robotic systems as well as current limitations of existing humanoid-robotic platforms.
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.
Emerging technology, especially robotic technology, has been shown to be appealing to children with autism spectrum disorders (ASD). Such interest may be leveraged to provide repeatable, accurate and individualized intervention services to young children with ASD based on quantitative metrics. However, existing robot-mediated systems tend to have limited adaptive capability that may impact individualization. Our current work seeks to bridge this gap by developing an adaptive and individualized robot-mediated technology for children with ASD. The system is composed of a humanoid robot with its vision augmented by a network of cameras for real-time head tracking using a distributed architecture. Based on the cues from the child’s head movement, the robot intelligently adapts itself in an individualized manner to generate prompts and reinforcements with potential to promote skills in the ASD core deficit area of early social orienting. The system was validated for feasibility, accuracy, and performance. Results from a pilot usability study involving six children with ASD and a control group of six typically developing (TD) children are presented.
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.
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.
Social impairment is a core feature of schizophrenia that presents a major barrier toward recovery. Some of the psychotic symptoms are partly ameliorated by medication but the route to recovery is hampered by social impairments. Since existing social skills interventions tend to suffer from lack of availability, high-burden and low adherence, there is a dire need for an effective, alternative strategy. The present study examined the feasibility and acceptability of Multimodal Adaptive Social Intervention in Virtual Reality (MASI-VR) for improving social functioning and clinical outcomes in schizophrenia. Out of eighteen patients with schizophrenia who enrolled, seventeen participants completed the pre-treatment assessment and 10 sessions of MASI-VR, but one patient did not complete the post-treatment assessments. Therefore, the complete training plus pre- and post-treatment assessment data are available from sixteen participants. Clinical ratings of symptom severity were obtained at pre- and post-training. Retention rates were very high and training was rated as extremely satisfactory for the majority of participants. Participants exhibited a significant reduction in overall clinical symptoms, especially negative symptoms following 10 sessions of MASI-VR. These preliminary results support the feasibility and acceptability of a novel virtual reality social skills training program for individuals with schizophrenia.
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.
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