Social skills training for children with autism spectrum disorder using a robotic behavioral intervention system

Interactive mirrOring Games wIth sOCial rObot (IOGIOCO): a pilot study on the use of intransitive gestures in a sample of Italian preschool children with autism spectrum disorder

Background

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent deficits in social communication, social interaction, and restricted behaviors. The importance of early intervention has been widely demonstrated, and developmental trajectories in ASD emphasize the importance of nonverbal communication, such as intransitive gesture production, as a possible positive prognostic factor for language development. The use of technological tools in the therapy of individuals with ASD has also become increasingly important due to their higher engagement and responsiveness to technological objects, such as robots.

Materials and methods

We developed a training protocol using the humanoid robot NAO, called IOGIOCO (Interactive mirroring Games wIth sOCial rObot), based on the use of intransitive gestures embedded in naturalistic dialogues, stimulating a triadic interaction between child, robot and therapist. The training was divided into six levels; the first 2 levels were called "familiarization levels," and the other 4 were "training levels". The technological setup includes different complexity levels, from mirroring tasks to building spontaneous interactions. We tested the protocol on 10 preschool children with ASD (aged 2-6 years) for 14 weeks. We assessed them at recruitment (T0), at the end of training (T1), and after 6 months (T2).

Results

We demonstrated the tolerability of the protocol. We found that one group (n=4, males and 2 females) reached the training level, while another and group (n=6 males) remained at a familiarization level (mirroring), we analyzed the results for the two groups. In the group that reached the training levels, we found promising results, such as an improvement in the Social Adaptive Domain of the ABAS-II questionnaire between T0 and T2.

Conclusion

While current results will need a Randomized Controlled Trial to be confirmed, the present work sets an important milestone in using social robots for ASD treatment, aimed at impacting social and communication skills in everyday life.

Effectiveness of a Robot-Assisted Psychological Intervention for Children with Autism Spectrum Disorder

Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The main aim of this randomised controlled study was to evaluate the effectiveness of a robot-assisted psychosocial intervention and the secondary aim was to investigate potential differences between a robot-assisted intervention group and a control group receiving intervention by humans only. The analysis of the results showed that robot-assisted intervention could be beneficial by improving children's psychosocial skills. This improvement was highlighted by neuropsychological testing and parent reporting. Group comparison only presented minimal statistically significant differences. The study underpins the potential of robot-assisted interventions to augment standard care.

A Scoping Review of the Use of Robotics Technologies for Supporting Social-Emotional Learning in Children with Autism

This scoping review synthesises the current research into robotics technologies for promoting social-emotional learning in children with autism spectrum disorder. It examines the types of robotics technologies employed, their applications, and the gaps in the existing literature. Our scoping review adhered to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) reporting guidelines. The systematic search of relevant databases allowed us to identify studies that use robotics technologies for fostering social, emotional, and cognitive skills in young children with autism. Our review has revealed that various robots, such as Nao, Kaspar, and Zeno, have been used to support the development of social and emotional skills through imitation games, turn-taking, joint attention, emotional recognition, and conversation. As most of these studies were conducted in clinical settings, there is a need for further research in classroom and community-based environments. Additionally, the literature calls for more high-quality longitudinal studies to assess the long-term effectiveness and sustainability of robot-assisted therapy and to assess adaptive and personalised interventions tailored to individual needs. More emphasis is recommended on professional development for educators, parents, and health professionals to incorporate robotics technologies as evidence-based interventions as a pathway for creating inclusive learning environments for children with autism.

Information and communication technologies-based interventions for children with autism spectrum conditions: a systematic review of randomized control trials from a positive technology perspective

Information and communication technologies (ICTs) have become more widely used in the past years to help people with autism spectrum conditions (ASC). Serious games embedded into computers or tablets, as well as social robots, are the most employed ICT-related tools that are appealing to and appropriate for autistic children. The goal of ICT applications is to enhance behavioral abnormalities associated with ASC while also creating an interactive link between one person and one computer. Comparatively, to human-based therapy, ICT tools aid to inspire autistic children by providing predictability and regularity of tasks. Regaining social skills is the primary behavioral goal for which ICT tools have been designed and implemented. In the past several years, many studies have been created to show how effective it is at improving targeted behaviors. However, only a small number of researchers have used an RCT approach to evaluate its effectiveness. In this systematic review, we only included RCT studies where ICT technologies were used to help children with ASC in improving their social skills. Only 14 RCT studies satisfied the criteria and 12 described significant improvements, showing how the use of technology in educational contexts produced better improvement in developing several social skill facets with respect to the traditional face-to-face approach. Some studies used interventions and outcome measures focused on the core ASC symptoms, but many others addressed neurocognitive functions directly, like social cognition or emotional regulation, while other more general functions such as language or adaptive behaviors. We propose a classification based on processes and outcome measures to foster future research in this specific area of research. The behavioral intervention mediated by technological tools such as computer-based, tablet, and social robotics, undoubtedly provides a comfortable environment that promotes constant learning for people with ASC. Evidence provided in this review highlights the translational potential of this field of study in primary care practice and educational settings.

A Scoping Review of Behavioral Interventions for Promoting Social Gaze in Individuals with Autism Spectrum Disorder and Other Developmental Disabilities

Background

Individuals diagnosed with autism spectrum disorder (ASD) commonly experience difficulties maintaining social gaze with others during interactions. Although behavioral interventions targeted to promote social gaze in ASD are evident in the literature, to our knowledge, no review of the literature has been conducted to summarize and evaluate the evidence for these interventions.

Methods

We reviewed and summarized behavioral intervention studies designed to promote social gaze in individuals diagnosed with ASD and other developmental disabilities published in English between 1977 and January 2022 using PsychINFO and PubMed databases.

Results

41 studies met the inclusion criteria describing interventions conducted on 608 individuals. A variety of intervention strategies were employed to promote social gaze in these individuals including discrete trial instruction, prompting, modeling, and imitation. Most studies employed single-case research designs and reported successful outcomes, but limited data were available concerning the generalization, maintenance and social validity of these interventions. An increasing number of studies utilized technology-based procedures including computer application gameplay, gaze-contingent eye tracking devices and humanoid robots.

Conclusions

The present review indicates that behavioral interventions can be successfully employed to promote social gaze in individuals with ASD and other developmental disabilities. However, future research is needed to establish the generalization, maintenance and social validity of these interventions. There are also important ethical issues to be addressed given the increasing divide between treatment advocates and proponents of the neurodiversity movement.

SD, Munera M, Casas D, Villa-Moreno A, Frizera-Neto A, Stoelen MF, Belpaeme T, Cifuentes CA. Do different robot appearances change emotion recognition in children with ASD?

Introduction

Socially Assistive Robotics has emerged as a potential tool for rehabilitating cognitive and developmental disorders in children with autism. Social robots found in the literature are often able to teach critical social skills, such as emotion recognition and physical interaction. Even though there are promising results in clinical studies, there is a lack of guidelines on selecting the appropriate robot and how to design and implement the child-robot interaction.

Methods

This work aims to evaluate the impacts of a social robot designed with three different appearances according to the results of a participatory design (PD) process with the community. A validation study in the emotion recognition task was carried out with 21 children with autism.

Results

Spectrum disorder results showed that robot-like appearances reached a higher percentage of children's attention and that participants performed better when recognizing simple emotions, such as happiness and sadness.

Discussion

This study offers empirical support for continuing research on using SAR to promote social interaction with children with ASD. Further long-term research will help to identify the differences between high and low-functioning children.

Extended reality for mental health: Current trends and future challenges

Virtual and augmented reality have been used to diagnose and treat several mental health disorders for decades. Technological advances in these fields have facilitated the availability of commercial solutions for end customers and practitioners. However, there are still some barriers and limitations that prevent these technologies from being widely used by professionals on a daily basis. In addition, the COVID-19 pandemic has exposed a variety of new scenarios in which these technologies could play an essential role, like providing remote treatment. Disorders that traditionally had received less attention are also getting in the spotlight, such as depression or obsessive-compulsive disorder. Improvements in equipment and hardware, like Mixed Reality Head Mounted Displays, could help open new opportunities in the mental health field. Extended reality (XR) is an umbrella term meant to comprise Virtual reality (VR), mixed reality (MR), and augmented reality (AR). While XR applications are eminently visual, other senses are being explored in literature around multisensory interactions, such as auditory, olfactory, or haptic feedback. Applying such stimuli within XR experiences around mental disorders is still under-explored and could greatly enrich the therapeutic experience. This manuscript reviews recent research regarding the use of XR for mental health scenarios, highlighting trends, and potential applications as well as areas for improvement. It also discusses future challenges and research areas in upcoming topics such as the use of wearables, multisensory, and multimodal interaction. The main goal of this paper is to unpack how these technologies could be applied to XR scenarios for mental health to exploit their full potential and follow the path of other health technologies by promoting personalized medicine.

Robot-mediated interventions for teaching children with ASD: A new intraverbal skill

Socially assistive robots (SAR) have the potential to impact therapies for Autism Spectrum Disorder (ASD) by supporting clinicians in increasing learning opportunities presented to individuals. Recent research on robot-mediated intervention (RMI) delivery has predominantly addressed social deficits in ASD with positive outcomes. Current literature has minimal focus on teaching children with ASD a skill not known apriori by the individual. Furthermore, it is unclear how to integrate robots in clinical settings because current RMIs do not adhere to Applied Behavior Analysis (ABA) protocols. In this work, we investigated whether an RMI could be utilized to teach children with ASD a completely new language and communication skill they could not exhibit at baseline. We utilized a standard ABA assessment tool to first identify appropriate skills to teach children with ASD. We then developed, implemented, and evaluated an RMI intervention that followed standard clinical operating procedures in ABA and targets participants' unique skill deficits. We examined the effects of the RMI training on teaching wh-question answering. All sessions were conducted with the SAR as the primary therapist using evidenced-based ABA human teaching protocols. All participants acquired the wh-questions answering skill within seven sessions, which is in line with their typical acquisition rates.

Social Humanoid Robots for Children with Autism Spectrum Disorders: A Review of Modalities, Indications, and Pitfalls

Robot-assisted therapy (RAT) is a promising area of translational neuroscience for children with autism spectrum disorders (ASDs). It has been widely demonstrated that this kind of advanced technological tool provides a reliable and efficient intervention for promoting social skills and communication in children with ASD. This type of treatment consists of a human-assisted social robot acting as an intervention mediator to increase competence and skills in children with ASD. Several social robots have been validated in the literature; however, an explicit technical comparison among devices has never been performed. For this reason, in this article, we provide an overview of the main commercial humanoid robots employed for ASD children with an emphasis on indications for use, pitfalls to be avoided, and recent advances. We conclude that, in the near future, a new generation of devices with high levels of mobility, availability, safety, and acceptability should be designed for improving the complex triadic interaction among teachers, children, and robots.

The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis

Background

Robot-mediated interventions show promise in supporting the development of children on the autism spectrum.

Objectives

In this systematic review and meta-analysis, we summarize key features of available evidence on robot-interventions for children and young people on the autism spectrum aged up to 18 years old, as well as consider their efficacy for specific domains of learning.

Data sources

PubMed, Scopus, EBSCOhost, Google Scholar, Cochrane Library, ACM Digital Library, and IEEE Xplore. Grey literature was also searched using PsycExtra, OpenGrey, British Library EThOS, and the British Library Catalogue. Databases were searched from inception until April (6th) 2021.

Synthesis methods

Searches undertaken across seven databases yielded 2145 articles. Forty studies met our review inclusion criteria of which 17 were randomized control trials. The methodological quality of studies was conducted with the Quality Assessment Tool for Quantitative Studies. A narrative synthesis summarised the findings. A meta-analysis was conducted with 12 RCTs.

Results

Most interventions used humanoid (67%) robotic platforms, were predominantly based in clinics (37%) followed home, schools and laboratory (17% respectively) environments and targeted at improving social and communication skills (77%). Focusing on the most common outcomes, a random effects meta-analysis of RCTs showed that robot-mediated interventions significantly improved social functioning (g = 0.35 [95%CI 0.09 to 0.61; k = 7). By contrast, robots did not improve emotional (g = 0.63 [95%CI -1.43 to 2.69]; k = 2) or motor outcomes (g = -0.10 [95%CI -1.08 to 0.89]; k = 3), but the numbers of trials were very small. Meta-regression revealed that age accounted for almost one-third of the variance in effect sizes, with greater benefits being found in younger children.

Conclusions

Overall, our findings support the use of robot-mediated interventions for autistic children and youth, and we propose several recommendations for future research to aid learning and enhance implementation in everyday settings.

PROSPERO registration

Our methods were preregistered in the PROSPERO database (CRD42019148981).

Social Robot Interventions in Mental Health Care and Their Outcomes, Barriers, and Facilitators: Scoping Review

BACKGROUND

The use of social robots as innovative therapeutic tools has been increasingly explored in recent years in an effort to address the growing need for alternative intervention modalities in mental health care.

OBJECTIVE

The aim of this scoping review was to identify and describe social robot interventions in mental health facilities and to highlight their outcomes as well as the barriers and facilitators to their implementation.

METHODS

A scoping review of the literature published since 2015 was conducted using the Arksey and O'Malley's framework. The MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO databases were searched, and 2239 papers were retrieved. The papers included were primary empirical studies published in peer-reviewed literature. Eligible studies were set in mental health facilities and they included participants with a known mental health disorder. The methodological quality of the included papers was also assessed using the Mixed Methods Appraisal Tool.

RESULTS

A total of 30 papers met the eligibility criteria for this review. Studies involved participants with dementia, cognitive impairment, schizophrenia, depression, autism spectrum disorder, attention-deficit hyperactivity disorder, and an intellectual disability. The outcomes studied included engagement, social interaction, emotional state, agitation, behavior, and quality of life.

CONCLUSIONS

The methodological weaknesses of the studies conducted this far and the lack of diversity in the conditions studied limit the generalizability of the results. However, despite the presence of certain barriers to their implementation (eg, technical problems, unsuitable environment, staff resistance), social robot interventions generally show positive effects on patients with mental health disorders. Studies of stronger methodological quality are needed to further understand the benefits and the place of social robots in mental health care.

EYE-C: Eye-Contact Robust Detection and Analysis during Unconstrained Child-Therapist Interactions in the Clinical Setting of Autism Spectrum Disorders

The high level of heterogeneity in Autism Spectrum Disorder (ASD) and the lack of systematic measurements complicate predicting outcomes of early intervention and the identification of better-tailored treatment programs. Computational phenotyping may assist therapists in monitoring child behavior through quantitative measures and personalizing the intervention based on individual characteristics; still, real-world behavioral analysis is an ongoing challenge. For this purpose, we designed EYE-C, a system based on OpenPose and Gaze360 for fine-grained analysis of eye-contact episodes in unconstrained therapist-child interactions via a single video camera. The model was validated on video data varying in resolution and setting, achieving promising performance. We further tested EYE-C on a clinical sample of 62 preschoolers with ASD for spectrum stratification based on eye-contact features and age. By unsupervised clustering, three distinct sub-groups were identified, differentiated by eye-contact dynamics and a specific clinical phenotype. Overall, this study highlights the potential of Artificial Intelligence in categorizing atypical behavior and providing translational solutions that might assist clinical practice.

Experience with an Affective Robot Assistant for Children with Hearing Disabilities

This study presents an assistive robotic system enhanced with emotion recognition capabilities for children with hearing disabilities. The system is designed and developed for the audiometry tests and rehabilitation of children in a clinical setting and includes a social humanoid robot (Pepper), an interactive interface, gamified audiometry tests, sensory setup and a machine/deep learning based emotion recognition module. Three scenarios involving conventional setup, tablet setup and setup with the robot+tablet are evaluated with 16 children having cochlear implant or hearing aid. Several machine learning techniques and deep learning models are used for the classification of the three test setups and for the classification of the emotions (pleasant, neutral, unpleasant) of children using the recorded physiological signals by E4 wristband. The results show that the collected signals during the tests can be separated successfully and the positive and negative emotions of children can be better distinguished when they interact with the robot than in the other two setups. In addition, the children’s objective and subjective evaluations as well as their impressions about the robot and its emotional behaviors are analyzed and discussed extensively.

Enhance the Language Ability of Humanoid Robot NAO through Deep Learning to Interact with Autistic Children

Autism spectrum disorder (ASD) is a life-long neurological disability, and a cure has not yet been found. ASD begins early in childhood and lasts throughout a person’s life. Through early intervention, many actions can be taken to improve the quality of life of children. Robots are one of the best choices for accompanying children with autism. However, for most robots, the dialogue system uses traditional techniques to produce responses. Robots cannot produce meaningful answers when the conversations have not been recorded in a database. The main contribution of our work is the incorporation of a conversation model into an actual robot system for supporting children with autism. We present the use a neural network model as the generative conversational agent, which aimed at generating meaningful and coherent dialogue responses given the dialogue history. The proposed model shares an embedding layer between the encoding and decoding processes through adoption. The model is different from the canonical Seq2Seq model in which the encoder output is used only to set-up the initial state of the decoder to avoid favoring short and unconditional responses with high prior probability. In order to improve the sensitivity to context, we changed the input method of the model to better adapt to the utterances of children with autism. We adopted transfer learning to make the proposed model learn the characteristics of dialogue with autistic children and to solve the problem of the insufficient corpus of dialogue. Experiments showed that the proposed method was superior to the canonical Seq2sSeq model and the GAN-based dialogue model in both automatic evaluation indicators and human evaluation, including pushing the BLEU precision to 0.23, the greedy matching score to 0.69, the embedding average score to 0.82, the vector extrema score to 0.55, the skip-thought score to 0.65, the KL divergence score to 5.73, and the EMD score to 12.21.

Human-robot interaction for social skill development in children with ASD: A literature review

Human-robot interaction has been demonstrated to be a promising methodology for developing socio-communicational skills of children and adolescents with autism spectrum disorder (ASD). This paper systematically reviews studies that report experimental results on this topic published in scientific journals between the years 2010 and2018. A total of 1805 articles from various literature were filtered based on relevance and transparency. In the first set of criteria, article titles are screened and in the second both titles and abstracts. The final number of articles which were subsequently thoroughly reviewed was 32 (N = 32). The findings suggest that there are benefits in using human-robot interaction to assist with the development of social skills for children with ASD. Specifically, it was found that the majority of studies used humanoid robots, 64% relied on a small number of participants and sessions, while few of the studies included a control group or follow-up sessions. Based on these findings, this paper tried to identify areas that have not been extensively addressed to propose several directions for future improvements for studies in this field, such as control groups with typical developmental children, minimum number of sessions and participants, as well as standardization of criteria for assessing the level of functionality for ASD children.

Emotional Expression in Children With ASD: A Pre-Study on a Two-Group Pre-Post-Test Design Comparing Robot-Based and Computer-Based Training

Several studies have found a delay in the development of facial emotion recognition and expression in children with an autism spectrum condition (ASC). Several interventions have been designed to help children to fill this gap. Most of them adopt technological devices (i.e., robots, computers, and avatars) as social mediators and reported evidence of improvement. Few interventions have aimed at promoting emotion recognition and expression abilities and, among these, most have focused on emotion recognition. Moreover, a crucial point is the generalization of the ability acquired during treatment to naturalistic interactions. This study aimed to evaluate the effectiveness of two technological-based interventions focused on the expression of basic emotions comparing a robot-based type of training with a "hybrid" computer-based one. Furthermore, we explored the engagement of the hybrid technological device introduced in the study as an intermediate step to facilitate the generalization of the acquired competencies in naturalistic settings. A two-group pre-post-test design was applied to a sample of 12 children (M = 9.33; ds = 2.19) with autism. The children were included in one of the two groups: group 1 received a robot-based type of training (n = 6); and group 2 received a computer-based type of training (n = 6). Pre- and post-intervention evaluations (i.e., time) of facial expression and production of four basic emotions (happiness, sadness, fear, and anger) were performed. Non-parametric ANOVAs found significant time effects between pre- and post-interventions on the ability to recognize sadness [t ₍₁₎ = 7.35, p = 0.006; pre: M (ds) = 4.58 (0.51); post: M (ds) = 5], and to express happiness [t ₍₁₎ = 5.72, p = 0.016; pre: M (ds) = 3.25 (1.81); post: M (ds) = 4.25 (1.76)], and sadness [t ₍₁₎ = 10.89, p < 0; pre: M (ds) = 1.5 (1.32); post: M (ds) = 3.42 (1.78)]. The group^*time interactions were significant for fear [t ₍₁₎ = 1.019, p = 0.03] and anger expression [t ₍₁₎ = 1.039, p = 0.03]. However, Mann-Whitney comparisons did not show significant differences between robot-based and computer-based training. Finally, no difference was found in the levels of engagement comparing the two groups in terms of the number of voice prompts given during interventions. Albeit the results are preliminary and should be interpreted with caution, this study suggests that two types of technology-based training, one mediated via a humanoid robot and the other via a pre-settled video of a peer, perform similarly in promoting facial recognition and expression of basic emotions in children with an ASC. The findings represent the first step to generalize the abilities acquired in a laboratory-trained situation to naturalistic interactions.

Robotic Uses in Pediatric Care: A Comprehensive Review

PROBLEM

Advances in technology have made robotics acceptable in healthcare and medical environments. The aim of this literature review was to examine how the pediatric population can benefit from robotic therapy and assistance that are currently available or being developed in diverse settings.

ELIGIBILITY CRITERIA

English language full-text publications focusing on pediatric robotic therapy studies for infants and children under the age of 17 indexed in PubMed and CINAHL and published from 2008 to 2018.

SAMPLE

A total of 272 articles were identified, 69 full-text articles were retrieved and assessed for eligibility, and 21 studies were finally used in the literature review.

RESULTS

From 21 studies, all studies reviewed showed that children benefited from robotic therapies were 1) responsive to the therapies and 2) favored robot's presence since the robotic systems increased their attention and ability to participate in tasks. Due to small sample size, results were statistically inconclusive.

CONCLUSIONS

We identified positive findings, where utilizing pediatric robots played vital roles in assisting and enhancing current pediatric and NICU treatments. Overall, our findings suggested that more clinical trials would be essential, but the uses of robots may contribute to the future advancement in pediatric and neonatal healthcare.

IMPLICATIONS

These review and analysis can be used to inform healthcare environments where there is a room for applying robotic assistance, although most studies required further testing with larger sample size to validate their results. This suggests the need for further research for robotics in pediatric and neonatal healthcare.

Are social robots ready yet to be used in care and therapy of autism spectrum disorder: A systematic review of randomized controlled trials

Autism is a neurodevelopmental disorder that affects the everyday life of people who have this lifelong condition. Robots hold great promise for uplifting therapy and care of the affected population. We searched Scopus, Medline, ScienceDirect, Web of Science, and PubMed databases for randomized controlled trials that had evaluated robot use in the therapy of people with autism, to see how effective social robots have been incorporated in autism care. Out of 240 papers initially identified, 19 satisfied the inclusion criteria and were fully evaluated. Overall, 10 different robots were utilized in the trials, out of which, four were non-humanoids. The number of papers with positive results for using robots on the main and secondary parameters was 11 and 5, respectively. Three papers reported that robot groups did not achieve better results than others. Robots in the papers included here were mainly added as the "entertainment agent" to elicit greater engagement from the participants, which is understandable, as robots at this stage might not be ready yet to deliver high-end care.

Electroencephalographic Correlate of Mexican Spanish Emotional Speech Processing in Autism Spectrum Disorder: To a Social Story and Robot-Based Intervention

Socio-emotional impairments are key symptoms of Autism Spectrum Disorders. This work proposes to analyze the neuronal activity related to the discrimination of emotional prosodies in autistic children (aged 9 to 11-year-old) as follows. Firstly, a database for single words uttered in Mexican Spanish by males, females, and children will be created. Then, optimal acoustic features for emotion characterization will be extracted, followed of a cubic kernel function Support Vector Machine (SVM) in order to validate the speech corpus. As a result, human-specific acoustic properties of emotional voice signals will be identified. Secondly, those identified acoustic properties will be modified to synthesize the recorded human emotional voices. Thirdly, both human and synthesized utterances will be used to study the electroencephalographic correlate of affective prosody processing in typically developed and autistic children. Finally, and on the basis of the outcomes, synthesized voice-enhanced environments will be created to develop an intervention based on social-robot and Social Story^TM for autistic children to improve affective prosodies discrimination. This protocol has been registered at BioMed Central under the following number: ISRCTN18117434.

Emotion recognition impairments and social well-being following right-hemisphere stroke

Accurately recognizing and responding to the emotions of others is essential for proper social communication and helps bind strong relationships that are particularly important for stroke survivors. Emotion recognition typically engages cortical areas that are predominantly right-lateralized including superior temporal and inferior frontal gyri - regions frequently impacted by right-hemisphere stroke. Since prior work already links right-hemisphere stroke to deficits in emotion recognition, this research aims to extend these findings to determine whether impaired emotion recognition after right-hemisphere stroke is associated with worse social well-being outcomes. Eighteen right-hemisphere stroke patients (≥6 months post-stroke) and 21 neurologically healthy controls completed a multimodal emotion recognition test (Geneva Emotion Recognition Test - Short) and reported engagement in social/non-social activities and levels of social support. Right-hemisphere stroke was associated with worse emotion recognition accuracy, though not all patients exhibited impairment. In line with hypotheses, emotion recognition impairments were associated with greater loss of social activities after stroke, an effect that could not be attributed to stroke severity or loss of non-social activities. Impairments were also linked to reduced patient-reported social support. Results implicate emotion recognition difficulties as a potential antecedent of social withdrawal after stroke and warrant future research to test emotion recognition training post-stroke.

Social Skills Training for Autism Spectrum Disorder: a Meta-analysis of In-person and Technological Interventions

Social skills training (SST) for autism spectrum disorder (ASD) has traditionally focused on face-to-face (F2F-SST) interventions. Recently, Behavioral Intervention Technologies (BITs-SST) have been utilized to target social skills deficits using computer-based programs, avatars, and therapeutic robots. The present meta-analysis reviews recent evidence and compares the efficacy of 14 F2F-SST and four identified BITs-SST intervention trials for youth with ASD. These preliminary analyses did not indicate significant differences between F2F-SST and BITs-SST, with effect sizes consistently in the medium to high range (g = 0.81 and g = 0.93, respectively). These findings provide initial support for the continued investigation of BITs for providing SST to youth with ASD.

An Open-Source Social Robot Based on Compliant Soft Robotics for Therapy with Children with ASD

Therapy with robotic tools is a promising way to help improve verbal and nonverbal communication in children. The robotic tools are able to increase aspects such as eye contact and the ability to follow instructions and to empathize with others. This work presents the design methodology, development, and experimental validation of a novel social robot based on CompliAnt SofT Robotics called the CASTOR robot, which intends to be used as an open-source platform for the long-term therapy of children with autism spectrum disorder (CwASD). CASTOR integrates the concepts of soft actuators and compliant mechanisms to create a replicable robotic platform aimed at real therapy scenarios involving physical interaction between the children and the robot. The validation shows promising results in terms of robustness and the safety of the user and robot. Likewise, mechanical tests assess the robot’s response to blocking conditions for two critical modules (i.e., neck and arm) in interaction scenarios. Future works should focus on the validation of the robot’s effectiveness in the therapy of CwASD.

Brief Report: Neuroimaging Endophenotypes of Social Robotic Applications in Autism Spectrum Disorder

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism and predict treatment response. Social robotics has recently been proposed as an effective tool to strengthen the current treatments in children with autism. However, the high clinical heterogeneity characterizing this disorder might interfere with behavioral effects. Neuroimaging is set to overcome these limitations by capturing the level of heterogeneity. Here, we provide a preliminary evaluation of the neural basis of social robotics and how extracting neural hallmarks useful to design more effective behavioral applications. Despite the endophenotype-oriented neuroimaging research approach is in its relative infancy, this preliminary evidence encourages innovation to address its current limitations.

A systematic review evaluating the implementation of technologies to assess, monitor and treat neurodevelopmental disorders: A map of the current evidence

Technology-based interventions provide an attractive option for improving service provision for neurodevelopmental disorders (NDD), for example, widening access to interventions, objective assessment, and monitoring; however, it is unclear whether there is sufficient evidence to support their use in clinical settings. This review provides an evidence map describing how technology is implemented in the assessment/diagnosis and monitoring/ treatment of NDD (Prospero CRD42018091156). Using predefined search terms in six databases, 7982 articles were identified, 808 full-texts were screened, resulting in 47 included papers. These studies were appraised and synthesised according to the following outcomes of interest: effectiveness (clinical effectiveness/ service delivery efficiencies), economic impact, and user impact (acceptability/ feasibility). The findings describe how technology is currently being utilised clinically, highlights gaps in knowledge, and discusses future research needs. Technology has been used to facilitate assessment and treatment across multiple NDD, especially Autism Spectrum (ASD) and attention-deficit/hyperactivity (ADHD) disorders. Technologies include mobile apps/tablets, robots, gaming, computerised tests, videos, and virtual reality. The outcomes presented largely focus on the clinical effectiveness of the technology, with approximately half the papers demonstrating some degree of effectiveness, however, the methodological quality of many studies is limited. Further research should focus on randomised controlled trial designs with longer follow-up periods, incorporating an economic evaluation, as well as qualitative studies including process evaluations and user impact.

Collaborative Research Project: Developing and Testing a Robot-Assisted Intervention for Children With Autism

The present work is a collaborative research aimed at testing the effectiveness of the robot-assisted intervention administered in real clinical settings by real educators. Social robots dedicated to assisting persons with autism spectrum disorder (ASD) are rarely used in clinics. In a collaborative effort to bridge the gap between innovation in research and clinical practice, a team of engineers, clinicians and researchers working in the field of psychology developed and tested a robot-assisted educational intervention for children with low-functioning ASD (N = 20) A total of 14 lessons targeting requesting and turn-taking were elaborated, based on the Pivotal Training Method and principles of Applied Analysis of Behavior. Results showed that sensory rewards provided by the robot elicited more positive reactions than verbal praises from humans. The robot was of greatest benefit to children with a low level of disability. The educators were quite enthusiastic about children's progress in learning basic psychosocial skills from interactions with the robot. The robot nonetheless failed to act as a social mediator, as more prosocial behaviors were observed in the control condition, where instead of interacting with the robot children played with a ball. We discuss how to program robots to the distinct needs of individuals with ASD, how to harness robots' likability in order to enhance social skill learning, and how to arrive at a consensus about the standards of excellence that need to be met in interdisciplinary co-creation research. Our intuition is that robotic assistance, obviously judged as to be positive by educators, may contribute to the dissemination of innovative evidence-based practice for individuals with ASD.

Feasibility of autism-focused public speech training using a simple virtual audience for autism spectrum disorder

AIM

Public speaking seems to be one of the most anxiety-provoking situations for individuals with autism spectrum disorder (ASD). However, there are few evidence-based interventions. We developed Autism-Focused Public Speech Training using Simple Virtual Audiences (APSV), which differs from a general virtual audience in terms of its simple facial expressions and emphasis on the importance of the eyes. The present study aimed to evaluate the feasibility of APSV as an educational method for individuals with ASD.

METHODS

Fifteen male individuals with ASD were randomly assigned to two groups: one group received APSV (n = 8), and the other group (n = 7) received independent study (IS). From Days 2 to 6, participants in the APSV and IS groups were encouraged to read and answer questions often asked in actual public speaking events. Participants in the APSV study group performed this activity in front of the APSV system, while those in the IS group performed in an empty room. Before and after the intervention (Days 1 and 7), the participants in the two groups had a mock public speaking experience in front of 10 people for approximately 10 min.

RESULTS

After the training sessions, the participants' self-confidence had improved and salivary cortisol levels were significantly decreased in the APSV group as compared to those in the IS group. APSV improved self-confidence and decreased public speaking stress in individuals with ASD.

CONCLUSION

APSV appears to be useful in improving self-confidence and decreasing public speaking stress in individuals with ASD.

Review of assistive technology in the training of children with autism spectrum disorders

The use of socially assistive robotics (SARs) is a promising method for improving the social skills of children with autism spectrum disorder (ASD). Studies conducted in this field in recent years show that the use of robots as collaborators may have positive effects on the development of social skills in children with ASD, especially in those areas where they reveal great deficits. In this literature review, we present, organize and evaluate the most important features and results of 13 relevant scientific articles. In analysis of the research findings we explored the documented effectiveness of robotics in enhancing the social skills of children with ASD in the areas of mutual attention, verbal communication and imitation skills, and also in the reduction of stereotypical behavior. Analysis of the results of the 13 studies confirmed that robots can have positive immediate effects on the communication skills of children with ASD, which holds promise for future intervention programs and relevant research.

Relaxing Gaze Aversion of Adolescents With Autism Spectrum Disorder in Consecutive Conversations With Human and Android Robot-A Preliminary Study

Establishing a treatment method for individuals with autism spectrum disorder (ASD) not only to increase their frequency or duration of eye contact but also to maintain it after ceasing the intervention, and furthermore generalize it across communication partners, is a formidable challenge. Android robots, which are a type of humanoid robot with appearances quite similar to that of humans, are expected to adapt to the role of training partners of face-to-face communication for individuals with ASD and to create easier experiences transferrable to humans. To evaluate this possibility, four male adolescents with ASD and six without ASD were asked to participate a pilot experiment in which there were consecutive sessions of semistructured conversation where they alternately faced either a human female or a female-type android robot interlocutor five times in total. Although it is limited by the small sample size, the preliminary results of analysis of their fixation pattern during the conversations indicated positive signs; the subjects tended to look more at the face of the android robot than that of the human interlocutor regardless of whether they had ASD. However, the individuals with ASD looked more at the area around the eyes of the android robot than at the human, and also looked less at that of the human than the individuals without ASD did. An increasing tendency of looking at the area around the human eyes, which could be a positive sign of the transferability of the experiences with an android robot to a human interlocutor, was only weakly observed as the sessions progressed.

Psychosocial Health Interventions by Social Robots: Systematic Review of Randomized Controlled Trials

Background

Social robots that can communicate and interact with people offer exciting opportunities for improved health care access and outcomes. However, evidence from randomized controlled trials (RCTs) on health or well-being outcomes has not yet been clearly synthesized across all health domains where social robots have been tested.

Objective

This study aimed to undertake a systematic review examining current evidence from RCTs on the effects of psychosocial interventions by social robots on health or well-being.

Methods

Medline, PsycInfo, ScienceDirect, Scopus, and Engineering Village searches across all years in the English language were conducted and supplemented by forward and backward searches. The included papers reported RCTs that assessed changes in health or well-being from interactions with a social robot across at least 2 measurement occasions.

Results

Out of 408 extracted records, 27 trials met the inclusion criteria: 6 in child health or well-being, 9 in children with autism spectrum disorder, and 12 with older adults. No trials on adolescents, young adults, or other problem areas were identified, and no studies had interventions where robots spontaneously modified verbal responses based on speech by participants. Most trials were small (total N=5 to 415; median=34), only 6 (22%) reported any follow-up outcomes (2 to 12 weeks; median=3.5) and a single-blind assessment was reported in 8 (31%). More recent trials tended to have greater methodological quality. All papers reported some positive outcomes from robotic interventions, although most trials had some measures that showed no difference or favored alternate treatments.

Conclusions

Controlled research on social robots is at an early stage, as is the current range of their applications to health care. Research on social robot interventions in clinical and health settings needs to transition from exploratory investigations to include large-scale controlled trials with sophisticated methodology, to increase confidence in their efficacy.

ICT and autism care: state of the art

PURPOSE OF REVIEW

Over the past 10 years, the use of information and communication technologies (ICTs) has increased in regard to the treatment of individuals with autism spectrum disorders (ASDs). ICT support mechanisms (e.g. computers, laptops, robots) are particularly attractive and are adapted to children with ASD. In addition, ICT algorithms can offer new perspectives for clinicians, outside direct apps or gaming proposals. Here, we will focus on the use of serious games and robots because of their attractiveness and their value in working on social skills.

RECENT FINDINGS

The latest knowledge regarding the use of ICT in the forms of serious games and robotics applied to individuals with ASD shows that the field of serious games has already achieved interesting and promising results, although the clinical validations are not always complete. In the field of robotics, there are still many limitations on the use of ICT (e.g. most interaction are similar to the wizard of Oz), and questions remain concerning their eventual effectiveness.

SUMMARY

To describe the implications of the findings for clinical practice or research, we describe two large projects, namely, JEMImE and Michelangelo, as examples of current studies that are aimed at enhancing social skills in children with ASD by including novel algorithms with clinical insights in robots or serious games.

The impact of robotic intervention on joint attention in children with autism spectrum disorders

Background

A growing body of anecdotal evidence indicates that the use of robots may provide unique opportunities for assisting children with autism spectrum disorders (ASD). However, previous studies investigating the effects of interventions using robots on joint attention (JA) in children with ASD have shown insufficient results. The robots used in these studies could not turn their eyes, which was a limitation preventing the robot from resembling a human agent.

Methods

We compared the behavior of children with ASD with that of children with typical development (TD) during a JA elicitation task while the children interacted with either a human or a robotic agent. We used the robot "CommU," which has clear eyes and can turn its eyes, for the robotic intervention. The age range of the participants was limited to 5-6 years.

Results

Sixty-eight participants participated in this study, including 30 (10 females and 20 males) children with ASD and 38 (13 females and 25 males) children with TD. The participants were randomly assigned to one of the following two groups: the robotic intervention group or the control group. JA in the children with ASD was better during the robotic intervention than during the human agent intervention. These children exhibited improved performance in the JA task with human after interacting with the robot CommU. JA was differentially facilitated by the human and robotic agents between the ASD and TD children.

Conclusions

The findings of this study significantly contribute to the literature on the impact of robots on JA and provide information regarding the suitability of specific robot types for therapeutic use.

Robot-based intervention may reduce delay in the production of intransitive gestures in Chinese-speaking preschoolers with autism spectrum disorder

Background

Past studies have shown that robot-based intervention was effective in improving gestural use in children with autism spectrum disorders (ASD). The present study examined whether children with ASD could catch up to the level of gestural production found in age-matched children with typical development and whether they showed an increase in verbal imitation after the completion of robot-based training. We also explored the cognitive and motor skills associated with gestural learning.

Methods

Children with ASD were randomly assigned to two groups. Four- to 6-year-old children with ASD in the intervention group (N = 15) received four 30-min robot-based gestural training sessions. In each session, a social robot, NAO, narrated five stories and gestured (e.g., both hands clapping for an awesome expression). Children with ASD were told to imitate the gestures during training. Age-matched children with ASD in the wait-list control group (N = 15) and age-matched children with typical development (N = 15) received the gestural training after the completion of research. Standardized pretests and posttests (both immediate and delayed) were administered to assess the accuracy and appropriateness of gestural production in both training and novel stories. Children's language and communication abilities, gestural recognition skills, fine motor proficiencies, and attention skills were also examined.

Results

Children with ASD in the intervention condition were more likely to produce accurate or appropriate intransitive gestures in training and novel stories than those in the wait-list control. The positive learning outcomes were maintained in the delayed posttests. The level of gestural production accuracy in children with ASD in the delayed posttest of novel stories was comparable to that in children with typical development, suggesting that children with ASD could catch up to the level of gestural production found in children with typical development. Children with ASD in the intervention condition were also more likely to produce verbal markers while gesturing than those in the wait-list control. Gestural recognition skills were found to significantly predict the learning of gestural production accuracy in the children with ASD, with such relation partially mediated via spontaneous imitation.

Conclusions

Robot-based intervention may reduce the gestural delay in children with ASD in their early childhood.