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

Reading decoding and comprehension in children with autism spectrum disorders: Evidence from a language with regular orthography

Decoding and comprehension skills in children with autism spectrum disorders (ASD) were analysed in children native speakers of a language (Italian) with a highly regular orthography. Children with ASD were compared to children with matched intellectual functioning: a subgroup of children with ASD and borderline intellectual functioning (BIF) was compared to a subgroup of children with BIF but no signs of ASD; a subgroup of children with ASD and cognitive functioning within normal limits was compared to a group of typically developing children. Children with ASD (whether with or without BIF) showed essentially spared decoding skills in text as well as word and pseudo-word reading; this was at variance with children with BIF who, as a group, showed overall deficient decoding skills, despite considerable individual differences. By contrast, children with ASD (once again, irrespective of the presence of BIF) showed a selective impairment in reading comprehension, just like children with BIF but unlike the typically developing ones. Therefore, results are generally consistent with a profile of hyperlexia for children with ASD learning a regular orthography, as previously reported for other languages. Notably, this pattern was present irrespective of the degree of cognitive impairment, and clearly distinguished these children from those with borderline intellectual functioning but not signs of autism

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

GAUSSIAN MIXTURE MODELS FOR THE ANALYSIS OF WISC-IV DIMENSIONS: A MULTIVARIATE APPROACH TO IMPROVE THE ASSESSMENT OF INTELLECTUAL FUNCTIONING

The Wechsler Intelligence Scale for Children-IV provides four indexes that analyze the intellectual functioning in specific cognitive fields and a full-scale intelligence quotient (FSIQ) as a measure of the general cognitive ability. However, often the diagnostic process considers the FSIQ score only. This study exploits the Gaussian mixture model (GMM) as a statistical tool to analyze WISC-IV capability to support the diagnostic decision-making process in a multidimensional approach based on the joint evaluation of the four main indexes. The study was conducted on two groups of participants (10 and 12 years old with N=52 and N=47, respectively) with clinical diagnosis. In addition, N=50 observations were randomly generated from the distribution of the Italian reference populations referred to each age group. In both groups, GMM detected two components underlining different behaviors in central tendency, variability, and correlation. Comparison of GMM partitions with a supervised classification shows that group memberships are congruent

Adapting robot-assisted therapy of children with autism and different levels of intellectual disability

Autism Spectrum Disorder (ASD) is a complex developmental disorder that requires personalising the treatment to the personal condition, in particular for individuals with Intellectual Disability (ID), which are the majority of those with ASD. In this paper, we present a preliminary analysis of our on-going research on personalised care for children with ASD and ID. The investigation focuses on integrating a social robot within the standard treatment in which tasks and level of interaction are adapted to the ID level of the individual and follow his progress after the rehabilitation

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

Self-injurious behavior: A comparison between Prader-Willi syndrome, Down syndrome and Autism

Abstract The term Self-injurious Behavior (SIB

Spelling deficits in children with intellectual disabilities: Evidence from a regular orthography

IntroductionIn individuals with intellectual disabilities (ID), efficient reading and writing skills promote social integration, self-autonomy, and independence. However, research has mainly focused on reading skills, while evidence on spelling skills is scarce and mostly on English-speaking subjects. In the present research project, we compared the spelling skills of children with intellectual disabilities (ID) learning in Italian, a regular orthography, to those of typically developing children matched for school level.MethodsIn the first study, the performance on a Passage Dictation Test of forty-four children with ID attending regular classrooms from 4th to 8th grades (mean age = 12.16 years; SD = 1.57) were compared with controls matched for sex and grade. In the second study, a Words and Nonwords Dictation Test was administered (with stimuli varying for lexicality, orthographic complexity, regularity of transcription, and the presence of different types of phonetic-phonological difficulties) to twenty-two children with ID attending regular classrooms from 4th to 8th grades (mean age = 12.2 years; SD = 1.37) and 22 controls matched for sex and grade. In both studies, an error analysis was performed to characterize types of misspellings. Separate ANOVAs were performed on z scores.ResultsChildren with ID generally had a lower performance than controls. In the Passage Dictation Test, they showed a higher number of phonological (and phonetic-phonological) errors than phonologically plausible ones, indicating, as a group, predominant phonological difficulties as compared to lexical-orthographic ones. In the Words and Nonwords Dictation Test, they performed poorly on regular stimuli presenting specific types of phonetic-to-phonological difficulties (geminates, non-continuant consonants) and committed more minimal distance, context-sensitive and simple conversion misspellings. However, deficits in the orthographic-lexical procedure, as indicated by a low performance in words with unpredictable spelling, were present in a high percentage of children.DiscussionIt is concluded that children with ID have significant spelling difficulties not confined to the orthographic process but also in phoneme-to-grapheme mapping that, in a regular orthography like Italian, should be acquired early and easily

Robots in education and care of children with developmental disabilities : a study on acceptance by experienced and future professionals

Research in the area of robotics has made available numerous possibilities for further innovation in the education of children, especially in the rehabilitation of those with learning difficulties and/or intellectual disabilities. Despite the scientific evidence, there is still a strong scepticism against the use of robots in the fields of education and care of people. Here we present a study on the acceptance of robots by experienced practitioners (specialized in the treatment of intellectual disabilities) and university students in psychology and education sciences (as future professionals). The aim is to examine the factors, through the Unified Theory of Acceptance and Use of Technology (UTAUT) model, that may influence the decision to use a robot as an instrument in the practice. The overall results confirm the applicability of the model in the context of education and care of children, and suggest a positive attitude towards the use of the robot. The comparison highlights some scepticism among the practitioners, who perceive the robot as an expensive and limited tool, while students show a positive perception and a significantly higher willingness to use the robot. From this experience, we formulate the hypothesis that robots may be accepted if more integrated with standard rehabilitation protocols in a way that benefits can outweigh the costs

Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues