Can NAO Robot Improve Eye-Gaze Attention of Children with High Functioning Autism?

Presents the results of a preliminary study on understanding how humanoid robots can successfully improve social and communication skills among children with Autism Spectrum Disorders (ASD). Children with ASD experience deficits in appropriate verbal and nonverbal communication skills including motor control, emotional facial expressions, eye-gaze attention, and joint attention. Studies have shown that positive feedback from the robot on the participants' performance is an effective way to encourage children with ASD to communicate more. Other studies have also examined the use of affect recognition based on psycho physiological responses to modify the behaviors during a robotic game. However, there is limited information on the utility of humanoid robots' positive

Studying Facial Expression Recognition and Imitation Ability of Children with Autism Spectrum Disorder in Interaction with a Social Robot

Children with Autism Spectrum Disorder (ASD) experience limited abilities in recognizing non-verbal elements of social interactions such as facial expressions [1]. They also show deficiencies in imitating facial expressions in social situations. In this Master thesis, we focus on studying the ability of children with ASD in recognizing facial expressions and imitating the expressions using a rear-projected expressive humanoid robot, called Ryan. Recent studies show that social robots such as Ryan have great potential for autism therapy. We designed and developed three studies, first to evaluate the ability of children with ASD in recognizing facial expressions that are presented to them with different methods (i.e. robot versus video), and second to determine the effect of various methods on the facial expression imitation performance of children with ASD using Reinforcement Learning (RL). In the first study, we compared the facial expression recognition ability of children with ASD with Typically Developing (TD) children using Ryan. Overall, the results did not show a significant difference between the performance of the ASD and groups in expression recognition. The study revealed the significant effect of increasing the expression intensity level on the expression recognition accuracy. The study also revealed both groups perform significantly worse in recognizing fear and disgust expressions. The second study focused on the effect of context on the facial expression recognition ability of children with ASD compared to their TD peers. The result of this study showed a higher general performance of TD children compared to the ASD group. Within the TD group, fear and in the ASD group sadness were recognized with the lowest accuracy compared to the average accuracy of other expressions. The result of this study did not show any difference between groups; however, we found that there is a significant effect of different background categories in both groups. It means, we found a significant higher recognition accuracy for the negative backgrounds compared to positive backgrounds in 20% intensity for the fear and sadness expressions. In the third study, we designed an active learning method using RL algorithm to identify and adapt based on the individual differences in expression imitation in response to different conditions. We implemented the RL to first, identify the effective imitation method based on individual\u27s performance and preference; and second, to make an online adaptation and adjustment based on the effective method for each individual. The result of this study showed that the active learning method could successfully identify and adjust the session based on participant\u27s strength and preference. The results also showed that each participant responded differently to each method in general and for each expression

System Update: Technology Based Intervention for Students With Intellectual and Developmental Disabilities

Post-school outcomes are unfavorable to students with intellectual and developmental disabilities (IDD). Despite these outcomes and significant academic challenges, students with IDD have the potential to learn adaptive and life skills that lead to a more independent and fulfilling life through intentional intervention strategies. This dissertation explores technology-based interventions for students with IDD. Manuscript 1 presents a synthesis of literature related to technology, IDD, and a system of supports that schools utilize for tiered intervention delivery. Based on the findings, a new framework, Systems of Support for Technology Intervention (SSTI), is introduced to help guide school psychologists in choosing appropriate technology-based interventions based on tier and level of support. Manuscript 2 describes an AB single-participant case study examining a virtual reality intervention for a student with IDD. Review indicates that students with IDD benefit from (a) explicit instructional support (i.e., over-learning the behavior and techniques to maintain the behavior); (b) multiple opportunities to practice the skill (e.g., learning the skill in various environments); and (c) immediate and consistent feedback for skill development. Using a virtual reality program and best practices for intervention delivery, the participant learned how to independently shop in a grocery store setting. Results provide new directions and promising practices for school psychologists, including multi-modal instruction for skill acquisition and mastery. This dissertation hopes to be an applied research trailblazer in the field of school psychology for combining the uses of adaptive skill development, evidence-based practices, and innovative technology to teach students with IDD

Evaluation emotionaler und kommunikativer Verhaltensweisen in Mensch-Roboter Interaktionen in therapierelevanten Szenarien zur Entwicklung eines Modells für die roboterunterstützte Therapie bei Sprach- und Kommunikationsstörungen

Malchus K. Evaluation emotionaler und kommunikativer Verhaltensweisen in Mensch-Roboter Interaktionen in therapierelevanten Szenarien zur Entwicklung eines Modells für die roboterunterstützte Therapie bei Sprach- und Kommunikationsstörungen. Bielefeld: Universität Bielefeld; 2015