Deep learning systems for estimating visual attention in robot-assisted therapy of children with autism and intellectual disability

Recent studies suggest that some children with autism prefer robots as tutors for improving their social interaction and communication abilities which are impaired due to their disorder. Indeed, research has focused on developing a very promising form of intervention named Robot-Assisted Therapy. This area of intervention poses many challenges, including the necessary flexibility and adaptability to real unconstrained therapeutic settings, which are different from the constrained lab settings where most of the technology is typically tested. Among the most common impairments of children with autism and intellectual disability is social attention, which includes difficulties in establishing the correct visual focus of attention. This article presents an investigation on the use of novel deep learning neural network architectures for automatically estimating if the child is focusing their visual attention on the robot during a therapy session, which is an indicator of their engagement. To study the application, the authors gathered data from a clinical experiment in an unconstrained setting, which provided low-resolution videos recorded by the robot camera during the child–robot interaction. Two deep learning approaches are implemented in several variants and compared with a standard algorithm for face detection to verify the feasibility of estimating the status of the child directly from the robot sensors without relying on bulky external settings, which can distress the child with autism. One of the proposed approaches demonstrated a very high accuracy and it can be used for off-line continuous assessment during the therapy or for autonomously adapting the intervention in future robots with better computational capabilities

Social robots to support practitioners in the education and clinical care of children: The CARER-AID project

The Controlled Autonomous Robot for Early detection and Rehabilitation of Autism and Intellectual Disability (CARER-AID) project aimed at verifying the effects of the introduction of a humanoid robot in the clinical routine as a supervised autonomous assistant to support clinical staff in the care of individuals with Autism Spectrum Disorder (ASD) associated with Intellectual Disability (ID). The CARER-AID project was undertaken by a multidisciplinary team composed of experts in artificial intelligence and robotics and clinical psychologists experienced in the treatment of ID. The literature shows that children with ASD seem to prefer robotic devices over non-robotic instruments and indeed humans. Starting from this, CARER-AID clinical studies provided experimental evidence that demonstrated several potential benefits of robot-assisted therapy when treating children with neurodevelopmental disorders, such as ASD with or without ID. Alongside the study in a clinical setting, the project also investigated the acceptability and the attitudes towards social robotics in an educational context. The study evaluated the teachers' perception of introducing a humanoid robot in a kindergarten and the attitudes of children with Typical Development (TD) towards. The results of the clinical and educational studies showed the usefulness of social robotics in supporting practitioners in their interventions with both TD and neurodevelopmental disorders. The CARER-AID project offers a unitary vision of a robot that can serve in different aspects and levels of the care, from the education to the therapeutic rehabilitation, from assessment to monitoring of results, providing assistance to caregivers and professionals at school and in clinical settings

Affect Recognition in Autism: a single case study on integrating a humanoid robot in a standard therapy.

Autism Spectrum Disorder (ASD) is a multifaceted developmental disorder that comprises a mixture of social impairments, with deficits in many areas including the theory of mind, imitation, and communication. Moreover, people with autism have difficulty in recognising and understanding emotional expressions. We are currently working on integrating a humanoid robot within the standard clinical treatment offered to children with ASD to support the therapists. In this article, using the A-B-A' single case design, we propose a robot-assisted affect recognition training and to present the results on the child’s progress during the five months of clinical experimentation. In the investigation, we tested the generalization of learning and the long-term maintenance of new skills via the NEPSY-II affection recognition sub-test. The results of this single case study suggest the feasibility and effectiveness of using a humanoid robot to assist with emotion recognition training in children with ASD

An explorative study on robotics for supporting children with Autism Spectrum Disorder during clinical procedures

This short report presents a small-scale explorative study about children with Autism Spectrum Disorder (ASD) interaction with robots during clinical interactions. This is part of an ongoing project, which aims at defining a robotic service for supporting children with developmental disabilities and increase the efficiency of routine procedures that may create distress, e.g.having blood taken or an orthopaedic plaster cast applied. Five children with confirmed diagnoses of ASD interacted with two social robots: the small humanoid NAO and the pet-like MiRo. The encounters mixed play activities with a simulated clinical procedure. We included parents/carers in the interaction to ensure the child was comfortable and at ease. The results of video analysis and parents' feedback confirm possible benefits of the physical presence of robots to reduce children’s anxiety and increase compliance with instructions. Parents/carers convincingly support the introduction of robots in hospital procedures to their help children

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

Applications of Robotics for Autism Spectrum Disorder: a Scoping Review

Robotic therapies are receiving growing interest in the autism field, especially for the improvement of social skills of children, enhancing traditional human interventions. In this work, we conduct a scoping review of the literature in robotics for autism, providing the largest review on this field from the last five years. Our work underlines the need to better characterize participants and to increase the sample size. It is also important to develop homogeneous training protocols to analyse and compare the results. Nevertheless, 7 out of the 10 Randomized control trials reported a significant impact of robotic therapy. Overall, robot autonomy, adaptability and personalization as well as more standardized outcome measures were pointed as the most critical issues to address in future research

An empirical study on integrating a small humanoid robot to support the therapy of children with Autism Spectrum Disorder and intellectual disability

Recent research showed the potential benefits of robot-assisted therapy in treating children with Autism Spectrum Disorder. These children often have some form of Intellectual Disability (ID) too, but this has mainly been neglected by previous robotics research. This article presents an empirical evaluation of robot-assisted imitation training, where the child imitated the robot, integrated into the Treatment and Education of Autistic and related Communication handicapped Children (TEACCH) program. The sample included six hospitalized children with different levels of ID, from mild to profound. We applied mixed methods to assess their progress, during treatment and three months later. Results show increased Gross Motor Imitation skills in the children, except for those with profound ID and the therapists' positive attitude towards the humanoid robot. Furthermore, the therapists suggest how a robot could be used to autonomously collect and analyze the information obtained in the rehabilitation training for a continuous evaluation of the participants

Social robots for older users: a possibility to support assessment and social interventions

In the last decades, various researches in the field of robotics have created numerous opportunities for innovative support of the older population. The goal of this work was to review and highlight how social robots can help the daily life of older people, and be useful also as assessment tools. We will underline the aspects of usability and acceptability of robotic supports in the psychosocial work with older persons. The actual usability of the system influences the perception of the ease of use only when the user has no or low experience, while expert users’ perception is related to their attitude towards the robot. This finding should be more deeply analysed because it may have a strong influence on the design of future interfaces for elderly-robot interaction. Robots can play an important role to tackle the societal challenge of the growing older population. The authors report some recent studies with older users, where it was demonstrated that the acceptability of robotics during daily life activities, and also in cognitive evaluation, could be supported by social robot