Emilia Emilia Barakova

Promoting question-asking in school-aged children with autism spectrum disorders: Effectiveness of a robot intervention compared to a human-trainer intervention

Objective: The purpose of the present study was to investigate the effectiveness of an applied behaviour analysis (ABA)-based intervention conducted by a robot compared to an ABA-based intervention conducted by a human trainer in promoting self-initiated questions in children with autism spectrum disorder (ASD). Methods: Data were collected in a combined crossover multiple baseline design across participants. Six children were randomly assigned to two experimental groups. Results: Results revealed that the number of self-initiated questions for both experimental groups increased between baseline and the first intervention and was maintained during follow-up. The high number of self-initiated questions during follow-up indicates that both groups maintained this skill. Conclusions: The interventions conducted by a robot and a human trainer were both effective in promoting self-initiated questions in children with ASD. No conclusion with regard to the differential effectiveness of both interventions could be drawn. Implications of the results and directions for future research are discussed.

End-user programming architecture facilitates the uptake of robots in social therapies

This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations. It aims to facilitate the uptake and actual use of robot technologies in therapies for training social skills to autistic children. However, the framework is easy to generalize for an arbitrary human–robot interaction application, where users with no technical background need to program robots, i.e. in various assistive robotics applications. We identified the main needs of end-user programming of robots as a basic prerequisite for the uptake of robots in assistive applications. These are reusability, modularity, affordances for natural interaction and the ease of use. After reviewing the shortcomings of the existing architectures, we developed an initial architecture according to these principles and embedded it in a robot platform. Further, we used a co-creation process to develop and concretize the architecture to facilitate solutions and create affordances for robot specialists and therapists. Several pilot tests showed that different user groups, including therapists with general computer skills and adolescents with autism could make simple training or general behavioral scenarios within 1 h, by connecting existing behavioral blocks and by typing textual robot commands for fine-tuning the behaviors. In addition, this paper explains the basic concepts behind the TiViPE based robot control platform, and gives guidelines for choosing the robot programming tool and designing end-user platforms for robots.

Creating Robots with Personality: The Effect of Personality on Social Intelligence

This study investigates the effect of two personality traits, dominance and extroversion, on social intelligence. To test these traits, a NAO robot was used, which was teleoperated through a computer using a Wizard of Oz technique. A within-subject design was conducted with extroversion as within-subject variable and dominance as between-subject. Participants were asked to cooperate with the robot to play “Who wants to be a millionaire”. Before the experiment participants filled in a personality questionnaire to measure their dominance and extroversion. After each condition, participants filled in a modified version of the Godspeed questionnaire concerning personality traits of the robot plus 4 extra traits related to social intelligence. The results reveal a significant effect of dominance and extroversion on social intelligence. The extrovert robot was judged as more socially intelligent, likeable, animate, intelligent and emotionally expressive than the introvert robot. Similarly, the submissive robot was characterized as more socially intelligent, likeable and emotionally expressive than the dominant robot. We found no substantial results towards the similarity-attraction hypothesis and therefore we could not make a conclusion about the mediating effect of participant” s personality on likeability.

Designing robot-assisted Pivotal Response Training in game activity for children with autism

Robot assisted therapy for patients with autism is promising, but there is a need for well designed studies that combine expert knowledge from the field of robotics and autism. Here, an iterative, participatory design process of robot assisted Pivotal Response Training (PRT) for autism therapy is presented. The scenarios for the robot assisted PRT intervention were created using a scenario based design approach through intensive collaboration between robot engineer and therapist. The developed scenarios were then represented in a hierarchical model using Activity Theory. Based on that model, the PRT intervention was implemented by the end-user programming software and evaluated with a child with autism. The scenario based design and the use of Activity Theory framework considerably speeded up the scenario creation process and the redesign time needed between the pilots compared to our previous experiments.

StepByStep: Design of an Interactive Pictorial Activity Game for Teaching Generalization Skills to Children with Autism

Translating acquired behavioral skills from training environments to daily-life situations is difficult for children with autism. This study introduces the StepByStep platform, in which pictorial activity schedules are implemented. Design decisions that increase the sameness in the environment and the comfort of the children were implemented to isolate the learning task and promote the training of generalization skills. Differently from existing visual scheduling systems, we use photographs of the child that is trained instead of general activity pictures. The design promotes the features of easy individualization of the training and of playfulness while learning. StepByStep was used by one participant in a pilot study, who showed behavior acquisition and translation to real life situations.

Development of a Robot-Based Environment for Training Children with Autism

This study is done as a part of design-research processes that aims to co-create technology supported robot centered therapy environment for autistic children. We attempt to evaluate to which extent the therapists who perform behavioral training of children with autism can be supported by robot technology in the process of therapy content creation and training. First, we feature a robot-centered environment that is technically designed to decrease the complexity of programming dynamic, synchronous and parallel interactive robot behavior to a level compatible with content creation. Afterwards, we apply the Cognitive Dimensions Framework CDF approach for evaluation of the usability of this environment that is employed to control a robot interacting with children with Autism Spectrum Disorders ASD. A pilot test with therapists of two clinics followed by a test with adolescents with autism was performed. Participants in the pilot test performed tasks according to the different types of user activity in the CDF, and answered a questionnaire corresponding with the different dimensions. The results show negative attitude towards one particular dimension, but also high scores in other dimensions. As an additional validation of the usability of the environment, 9 adolescents with ASD could also create robot scenarios. We interpret these results as follows. In general, the therapists and autistic adolescents could program relatively simple behavioral scenarios with robots. However, we need to further explore whether assembling and executing of more complex robot scenarios such as programming of dynamic real-life behaviors and task scheduling is possible by end-users.

Interplay between Natural and Artificial Intelligence in Training Autistic Children with Robots

The need to understand and model human-like behavior and intelligence has been embraced by a multidisciplinary community for several decades. The success so far has been shown in solutions for a concrete task or a competence, and these solutions are seldom a truly multidisciplinary effort. In this paper we analyze the needs and the opportunities for combining artificial intelligence and bio-inspired computation within an application domain that provides a cluster of solutions instead of searching for a solution to a single task. We analyze applications of training children with autism spectrum disorder (ASD) with a humanoid robot, because it must include multidisciplinary effort and at the same time there is a clear need for better models of human-like behavior which will be tested in real life scenarios through these robots. We designed, implemented, and carried out three applied behavior analysis (ABA) based robot interventions. All interventions aim to promote self initiated social behavior in children with ASD. We found out that the standardization of the robot training scenarios and using unified robot platforms can be an enabler for integrating multiple intelligent and bio-inspired algorithms for creation of tailored, but domain specific robot skills and competencies. This approach might set a new trend to how artificial and bio-inspired robot applications develop. We suggest that social computing techniques are a pragmatic solution to creation of standardized training scenarios and therefore enable the replacement of perceivably intelligent robot behaviors with truly intelligent ones.

Brain-inspired robots for autistic training and care

An increasing number of projects world-wide investigate the possibilities to include robots as a part of assessment and therapy practices for individuals with autism. There are two major reasons for that: the special interest of the autistic people in robots and electronic tools and the rapid developments in the multidisciplinary studies on the nature of social interaction and on autism as atypical social behavior.

Grounding emotions in robots - An introduction to the special issue

Robots inhabiting human environments need to act in relation to their own experience and embodiment as well as to social and emotional aspects. Robots that learn, act upon and incorporate their own experience and perception of others’ emotions into their responses make not only more productive artificial agents but also agents with whom humans can appropriately interact. This special issue seeks to address the significance of grounding of emotions in robots in relation to aspects of physical and homeostatic interaction in the world at an individual and social level. Specific questions concern: How can emotion and social interaction be grounded in the behavioral activity of the robotic system? Is a robot able to have intrinsic emotions? How can emotions, grounded in the embodiment of the robot, facilitate individually and socially adaptive behavior to the robot? This opening chapter provides an introduction to the articles that comprise this special issue and briefly discusses their relationship to grounding emotions in robots.

Rapid prototyping framework for robot-assisted training of autistic children

Research in uptake and actual use of robots in socially assistive tasks is rapidly growing. However, practical applications lack behind due to the enormous effort to create meaningful behaviours. This paper describes a rapid prototyping framework for robot-assisted training of children with Autism Spectrum Disorder (ASD). The main goal of this research is to provide a framework which translates the knowledge from the evidenced Pivotal Response Training to end-user tools, that allow therapists to program/adapt a training program mediated by a robot in order to use it in therapies. The overall structure of the intervention is based on Activity Theory which makes it easy to properly arrange robot actions and decisions. We appended a general end-user robot programming tool with PRT therapy-specific training structures which can be adapted with ease to create almost limitless learning opportunities utilizing a range of training scenarios or games. Pilot tests with children with ASD were performed to assess whether the robot assisted intervention created by this framework is ready for practical use. These showed that only minor adaptations were needed to increase the fluency of the robot-child interaction.