Musical Robots For Children With ASD Using A Client-Server Architecture

Presented at the 22nd International Conference on Auditory Display (ICAD-2016)People with Autistic Spectrum Disorders (ASD) are known to have difficulty recognizing and expressing emotions, which affects their social integration. Leveraging the recent advances in interactive robot and music therapy approaches, and integrating both, we have designed musical robots that can facilitate social and emotional interactions of children with ASD. Robots communicate with children with ASD while detecting their emotional states and physical activities and then, make real-time sonification based on the interaction data. Given that we envision the use of multiple robots with children, we have adopted a client-server architecture. Each robot and sensing device plays a role as a terminal, while the sonification server processes all the data and generates harmonized sonification. After describing our goals for the use of sonification, we detail the system architecture and on-going research scenarios. We believe that the present paper offers a new perspective on the sonification application for assistive technologies

Robot Assistive Therapy Strategies for Children with Autism

Background: Autism spectrum disorder (ASD) is a category of neurodevelopmental disorder characterized by persistent deficits in social communication and social interaction across multiple contexts as well as restricted, repetitive patterns of behaviour, interests, or activities. Social robots offer clinicians new ways to interact and work with people with ASD. Robot-Assisted Training (RAT) is a growing body of research in HRI, which studies how robots can assist and enhance human skills during a task-centred interaction. RAT systems have a wide range of application for children with ASD. Aims: In a pilot RCT with an experimental group and a control group, research aims will be: to assess group differences in repetitive and maladaptive behaviours (RMBs), affective states and performance tasks across sessions and within each group; to assess the perception of family relationships between two groups before and post robot interaction; to develop a robotic app capable to run Raven’s Progressive Matrices (RPM), a test typically used to measure general human intelligence and to compare the accuracy of the robot to capture the data with that run by psychologists. Material and Methods: Patients with mild or moderate level of ASD will be enrolled in the study which will last 3 years. The sample size is: 60 patients (30 patients will be located in the experimental group and 30 patients will be located in the control group) indicated by an evaluation of the estimated enrolment time. Inclusion criteria will be the following: eligibility of children confirmed using the Autism Diagnostic Observation Schedule −2; age ≥ 7 years; clinician judgment during a clinical psychology evaluation; written parental consent approved by the local ethical committee. The study will be conducted over 10 weeks for each participant, with the pretest and post test conducted during the first and last weeks of the study. The training will be provided over the intermediate eight weeks, with one session provided each week, for a total of 8 sessions. Baseline and follow-up evaluation include: socioeconomic status of families will be assessed using the Hollingshead scale; Social Communication Questionnaire (SCQ) will be used to screen the communication skills and social functioning in children with ASD; Vineland Adaptive Behavior Scale, 2nd edition (VABS) will be used to assess the capabilities of children in dealing with everyday life; severity and variety of children’s ripetitive behaviours will be also assessed using Repetitive Behavior Scale-Revised (RBS-R). Moreover, the perception of family relationships assessment will be run by Portfolio for the validation of parental acceptance and refusal (PARENTS). Expected Results: 1) improbe communication skills; 2) reduced repetitive and maladaptive behaviors; 3) more positive perception of family relationships; 4) improved performance. Conclusions: Robot-Assisted Training aims to train and enhance user (physical or cognitive) skills, through the interaction, and not assist users to complete a task thus a target is to enhance user performance by providing personalized and targeted assistance towards maximizing training and learning effects. Robotics systems can be used to manage therapy sessions, gather and analyse data and like interactions with the patient and generate useful information in the form of reports and graphs, thus are a powerful tool for the therapist to check patient’s progress and facilitate diagnosis

Robots and autistic children: a review

In accordance with the advancement in robotics and the scholarly literature, the extents of utilizing robots for autistic children are widened and could be a promising method for individual with Autism Spectrum Disorder (ASD) treatments, where the different form of robot (humanoid, non-humanoid, animal-like, toy, and kits) can be employed effectively as a support tool to augment the learning skills and rehabilitate of the individual with Autism Spectrum Disorder (ASD). Thus, the robots were exploited for ASD children in different aspects namely; modelling, teaching, and skills practicing; testing, highlighting and evaluating; providing feedback or encouragement; join Attention; eliciting social behaviours; emotion recognition and expression; imitation; vocalization; turn-taking; and diagnostic. The related literature published recently in journals and conferences is taken into account. In this paper, we review the use of robots that help in the therapy of individuals with Autism Spectrum Disorder (ASD). The articles on using robots for autistic children rehabilitation and education which reported results of experiments on a number of participants were implicated. After looking in digital libraries under this criteria, and excluding non-related, and duplicated studies, 39 studies have been found. The findings were focused mainly on the social communication skills of autistic children and how the extent of the robots mitigate their stereotyped behaviours. Deeper research is required in this area to cover all applications of robotic on autistic children in order to design feasible and low-cost robots that ensure provide high validity

A Robotic "Puppet Master" Application to ASD Therapeutic Support

This paper describes a preliminary work aimed at setting a therapeutic support for autistic teenagers using three humanoid robots NAO shared by ASD (Autism Spectrum Disorder) subjects. The studied population had attended successfully a first year program, and were observed with a second year program using the robots. This paper focuses on the content and the effects of the second year program. The approach is based on a master puppet concept: the subjects program the robots, and use them as an extension for communication. Twenty sessions were organized, alternating ten preparatory sessions and ten robotics programming sessions. During the preparatory sessions, the subjects write a story to be played by the robots. During the robot programming sessions, the subjects program the motions to be realized to make the robot tell the story. The program was concluded by a public performance. The experiment involves five ASD teenagers aged 12-15, who had all attended the first year robotics training. As a result, a progress in voluntary and organized communication skills of the five subjects was observed, leading to improvements in social organization, focus, voluntary communication, programming, reading and writing abilities. The changes observed in the subjects general behavior took place in a short time, and could be observed from one robotics session to the next one. The approach allowed the subjects to draw the limits of their body with respect to the environment, and therefore helped them confronting the world with less anxiety

Proprioceptive and Kinematic Profiles for Customized Human‐ Robot Interaction for People Suffering from Autism

In this chapter, we presented a method to define individual profiles in order to develop a new personalized robot‐based social interaction for individual with autistic spectrum disorder (ASD) with the hypothesis that hyporeactivity to visual motion and an overreliance on proprioceptive information would be linked to difficulties in integrating social cues and in engaging in successful interactions. We succeed to form three groups among our 19 participants (children, teenagers, and adults with ASD), describing each participant\u27s response to visual and proprioceptive inputs. We conducted a first experiment to present the robot Nao as a social companion and to avoid fear or stress toward the robot in future experiment. No direct link between the behavior of the participants toward the robot and their proprioceptive and visual profiles was observed. Still, we found encouraging results going in the direction of our hypothesis. In addition, almost all of our participants showed great interest to Nao. Defining such individual profiles prior to social interactions with a robot could provide promising strategies for designing successful and adapted human‐robot interaction (HRI) for individuals with ASD

The Key Artificial Intelligence Technologies in Early Childhood Education: A Review

Artificial Intelligence (AI) technologies have been applied in various domains, including early childhood education (ECE). Integration of AI educational technology is a recent significant trend in ECE. Currently, there are more and more studies of AI in ECE. To date, there is a lack of survey articles that discuss the studies of AI in ECE. In this paper, we provide an up-to-date and in-depth overview of the key AI technologies in ECE that provides a historical perspective, summarizes the representative works, outlines open questions, discusses the trends and challenges through a detailed bibliometric analysis, and provides insightful recommendations for future research. We mainly discuss the studies that apply AI-based robots and AI technologies to ECE, including improving the social interaction of children with an autism spectrum disorder. This paper significantly contributes to provide an up-to-date and in-depth survey that is suitable as introductory material for beginners to AI in ECE, as well as supplementary material for advanced users.Comment: 39 pages, 9 figures, 4 table

SOCIABOTS: A Robotic Approach for Special Education Children to Improve their Social Skills

Social behavior for special-needs children is crucial to ensure that the special-needs children know how to communicate and establish social relationship with others. Children with special-needs such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactive Disorder (ADHD), Down syndrome and Slow Learner usually have problems in socializing as they usually have empathy deficit. The current pedagogy used by teachers also are unattractive making them unable to attract the children’s attention and making them unable to stimulate the children’s kinetic senses and tactile senses thus affecting the learning rates of the special-needs children. Therefore, to address this issues, SOCIABOTS, a NAO robotic approach for the special education children to improve their social skills is developed as to aid teachers in their teaching process. This robotic application is able to play shapes game with the special-needs children and dance after they accomplish the task correctly. It is a perfect solution for both of the specialneeds children and the special education teachers as it caters both needs. This robotic module focuses on making learning turn taking attractive to sustain the special-needs children’ attention while stimulating their tactile and kinetic senses. The RAD methodology is used for development of this robotic module. Surveys, interviews and observations are the source of data to gather information and opinion for the development of SOCIABOTS. A shape recognition test is conducted to determine which background color works better in recognizing shapes. A field test at the Sekolah Kebangsaan Sultan Yussuf, Batu Gajah, Perak with 5 special education students was conducted to compare the effectiveness of SOCIABOTS against the current pedagogy used by teachers. The results show that SOCIABOTS helps in sustaining the specialneeds children’ attention and helps in assisting the teachers in teaching. It scores better compared to the current pedagogy that the teachers used in classes. This module is focusing on assisting teachers in their teaching process and helps special-needs children learning taking turns interactively thus improving their social skills

A Music-Therapy Robotic Platform for Children with Autism: A Pilot Study

Children with Autism Spectrum Disorder (ASD) experience deficits in verbal and nonverbal communication skills including motor control, turn-taking, and emotion recognition. Innovative technology, such as socially assistive robots, has shown to be a viable method for Autism therapy. This paper presents a novel robot-based music-therapy platform for modeling and improving the social responses and behaviors of children with ASD. Our autonomous social interactive system consists of three modules. Module one provides an autonomous initiative positioning system for the robot, NAO, to properly localize and play the instrument (Xylophone) using the robot’s arms. Module two allows NAO to play customized songs composed by individuals. Module three provides a real-life music therapy experience to the users. We adopted Short-time Fourier Transform and Levenshtein distance to fulfill the design requirements: 1) “music detection” and 2) “smart scoring and feedback”, which allows NAO to understand music and provide additional practice and oral feedback to the users as applicable. We designed and implemented six Human-Robot-Interaction (HRI) sessions including four intervention sessions. Nine children with ASD and seven Typically Developing participated in a total of fifty HRI experimental sessions. Using our platform, we collected and analyzed data on social behavioral changes and emotion recognition using Electrodermal Activity (EDA) signals. The results of our experiments demonstrate most of the participants were able to complete motor control tasks with 70% accuracy. Six out of the nine ASD participants showed stable turn-taking behavior when playing music. The results of automated emotion classification using Support Vector Machines illustrates that emotional arousal in the ASD group can be detected and well recognized via EDA bio-signals. In summary, the results of our data analyses, including emotion classification using EDA signals, indicate that the proposed robot-music based therapy platform is an attractive and promising assistive tool to facilitate the improvement of fine motor control and turn-taking skills in children with ASD

Impacts of using a social robot to teach music to children with low-functioning autism

This article endeavors to present the impact of conducting robot-assisted music-based intervention sessions for children with low-functioning (LF) autism. To this end, a drum/xylophone playing robot is used to teach basic concepts of how to play the instruments to four participants with LF autism during nine educational sessions. The main findings of this study are compared to similar studies conducted with children with high-functioning autism. Our main findings indicated that the stereotyped behaviors of all the subjects decreased during the course of the program with an approximate large Cohen’s d effect size. Moreover, the children showed some improvement in imitation, joint attention, and social skills from the Pre-Test to Post-Test. In addition, regarding music education, we indicated that while the children could not pass a test on the music notes or reading music phrases items because of their cognitive deficits, they showed acceptable improvements (with a large Cohen’s d effect size) in the Stambak Rhythm Reproduction Test, which means that some rhythm learning occurred for the LF participants. In addition, we indicated that parenting stress levels decreased during the program. This study presents some potential possibilities of performing robot-assisted interventions for children with LF autism