A Systematic Review of Research on Robot-Assisted Therapy for Children with Autism

Psychological variables related to technology-mediated intervention design in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder characterized by persistent impairments in communication, social interaction and learning (Hodges et al., 2020). Because of its heterogeneous nature, ASD presents complex challenges, including social exclusion, school abandonment and limited access to health care. Technologies offer a pragmatic solution to overcome these limitations and to deliver therapeutic interventions in both physical and online environments. Studies have demonstrated that technology-mediated interventions (TMIs) have a positive impact on the development of capabilities of individuals with ASD. However, according to the European Parliament's Research Service technologies for ASDs are less mature (European Parliament. Directorate General for Parliamentary Research Services., 2018) and the causes and effects of TMIs in ASD should be better understood.

AIMS

Present study aimed to investigate the psychological variables related to TMIs in ASD.

METHODS AND PROCEDURES

The study employed a survey research method with a between-subjects design involving 61 adult participants comprising therapists, teachers and parents of children with ASD and it examined psychological variables related to children with ASD, factors of technology usage, and parental and educators' experiences.

OUTCOMES AND RESULTS

The analysis of the data obtained from the questionnaire focused on correlations and differences between groups, and was carried out using nonparametric tests. Kendall's Tau B test was used to explore the relationships between variables. The Mann-Whitney nonparametric test was employed to identify differences between groups.

CONCLUSIONS AND IMPLICATIONS

The findings revealed numerous relationships between variables and meaningful differences between the groups investigated in terms of how technologies are perceived by stakeholders involved in ASD interventions.

Emergence of Artificial Intelligence Art Therapies (AIATs) in Mental Health Care: A Systematic Review

The application of artificial intelligence art therapies (AIATs) in mental health care represents an innovative merger between digital technology and the therapeutic potential of creative arts. This systematic review aimed to assess the effectiveness and ethical considerations of AIATs, incorporating robots, AI painting and AI Chatbots to augment traditional art therapies. Aligning with the Preferred Reporting Items for systematic reviews (PRISMA) guidelines, we meticulously searched PubMed, Cochrane Library, Web of Science and CNKI, resulting in 15 selected articles for detailed analysis. To ensure methodological quality, we applied the Joanna Briggs Institute (JBI) criteria for quality assessment and extracted data using the PICO(S) format, specifically targeting randomised controlled trials (RCTs). Our findings suggest that AIATs can profoundly enhance the therapeutic experience by providing new creative outlets and reinforcing existing methods, despite possible drawbacks and ethical challenges. This examination underscores AIATs' potential to enrich mental health therapies, emphasising the critical importance of ethical considerations and the responsible application of AI as the field evolves. With a focus on expanding treatment efficacy and patient expressiveness, the promise of AIATs in mental health care necessitates a careful balance between innovation and ethical responsibility. Trial Registration: PROSPERO: CRD42024504472.

Parental involvement in robot-mediated intervention: a systematic review

Introduction

Over the years, the conceptual approach to pediatric rehabilitation has reevaluated the parent's role in the therapeutic process, considering parental involvement as a necessary condition for the effectiveness of the intervention. In the field of pediatric intervention, the therapeutic use of robots represents a growing clinical interest, but the feasibility and applicability of these robotic interventions, including those involving parents, remain unclear. This systematic review aims to investigate parental involvement in robot-mediated interventions (RMI) for children and adolescents in the current literature. Our main goal is to analyze and summarize all existing studies to discuss and draw future research directions and implications for clinical practice.

Method

After collecting results from 1,106 studies, the studies selected were analyzed using thematic analysis. The literature review was conducted in accordance with the PRISMA guidelines by searching databases such as PubMed and Web of Science until 07 February 2023. Studies that met the following inclusion criteria were included: (1) the use of a robot as a therapeutic-rehabilitation tool and (2) the presence/involvement of parents/caregivers in child-robot therapeutic sessions.

Results

A total of 10 articles were included. The extracted data included study design, participant characteristics, type of robot used, outcome measures, aim, and type of intervention. The results reveal that parental involvement in RMI could be feasible and useful in improving intervention efficacy, particularly in improving the child's social-communicative abilities and the caregiver's educational skills.

Discussion

RMI intervention with parental participation could be a useful therapeutic strategy in pediatrics. However, to date, few studies have investigated this specific topic, and the reported results may enhance future research to understand its effectiveness in specific areas of use.

Systematic review registration

identifier: CRD42024553214.

Do we empathize humanoid robots and humans in the same way? Behavioral and multimodal brain imaging investigations

Humanoid robots have been designed to look more and more like humans to meet social demands. How do people empathize humanoid robots who look the same as but are essentially different from humans? We addressed this issue by examining subjective feelings, electrophysiological activities, and functional magnetic resonance imaging signals during perception of pain and neutral expressions of faces that were recognized as patients or humanoid robots. We found that healthy adults reported deceased feelings of understanding and sharing of humanoid robots' compared to patients' pain. Moreover, humanoid robot (vs. patient) identities reduced long-latency electrophysiological responses and blood oxygenation level-dependent signals in the left temporoparietal junction in response to pain (vs. neutral) expressions. Furthermore, we showed evidence that humanoid robot identities inhibited a causal input from the right ventral lateral prefrontal cortex to the left temporoparietal junction, contrasting the opposite effect produced by patient identities. These results suggest a neural model of modulations of empathy by humanoid robot identity through interactions between the cognitive and affective empathy networks, which provides a neurocognitive basis for understanding human-robot interactions.

Social robots in research on social and cognitive development in infants and toddlers: A scoping review

There is currently no systematic review of the growing body of literature on using social robots in early developmental research. Designing appropriate methods for early childhood research is crucial for broadening our understanding of young children's social and cognitive development. This scoping review systematically examines the existing literature on using social robots to study social and cognitive development in infants and toddlers aged between 2 and 35 months. Moreover, it aims to identify the research focus, findings, and reported gaps and challenges when using robots in research. We included empirical studies published between 1990 and May 29, 2023. We searched for literature in PsychINFO, ERIC, Web of Science, and PsyArXiv. Twenty-nine studies met the inclusion criteria and were mapped using the scoping review method. Our findings reveal that most studies were quantitative, with experimental designs conducted in a laboratory setting where children were exposed to physically present or virtual robots in a one-to-one situation. We found that robots were used to investigate four main concepts: animacy concept, action understanding, imitation, and early conversational skills. Many studies focused on whether young children regard robots as agents or social partners. The studies demonstrated that young children could learn from and understand social robots in some situations but not always. For instance, children's understanding of social robots was often facilitated by robots that behaved interactively and contingently. This scoping review highlights the need to design social robots that can engage in interactive and contingent social behaviors for early developmental research.

People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and Limits

Individuals with Autism Spectrum Disorder show deficits in communication and social interaction, as well as repetitive behaviors and restricted interests. Interacting with robots could bring benefits to this population, notably by fostering communication and social interaction. Studies even suggest that people with Autism Spectrum Disorder could interact more easily with a robot partner rather than a human partner. We will be looking at the benefits of robots and the reasons put forward to explain these results. The interest regarding robots would mainly be due to three of their characteristics: they can act as motivational tools, and they are simplified agents whose behavior is more predictable than that of a human. Nevertheless, there are still many challenges to be met in specifying the optimum conditions for using robots with individuals with Autism Spectrum Disorder.

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.

Breaking Barriers-The Intersection of AI and Assistive Technology in Autism Care: A Narrative Review

(Background) Autism increasingly requires a multidisciplinary approach that can effectively harmonize the realms of diagnosis and therapy, tailoring both to the individual. Assistive technologies (ATs) play an important role in this context and hold significant potential when integrated with artificial intelligence (AI). (Objective) The objective of this study is to analyze the state of integration of AI with ATs in autism through a review. (Methods) A review was conducted on PubMed and Scopus, applying a standard checklist and a qualification process. The outcome reported 22 studies, including 7 reviews. (Key Content and Findings) The results reveal an early yet promising interest in integrating AI into autism assistive technologies. Exciting developments are currently underway at the intersection of AI and robotics, as well as in the creation of wearable automated devices like smart glasses. These innovations offer substantial potential for enhancing communication, interaction, and social engagement for individuals with autism. Presently, researchers are prioritizing innovation over establishing a solid presence within the healthcare domain, where issues such as regulation and acceptance demand increased attention. (Conclusions) As the field continues to evolve, it becomes increasingly clear that AI will play a pivotal role in bridging various domains, and integrated ATs with AI are positioned to act as crucial connectors.

Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder

Background

Artificial intelligence (AI) has been the subject of studies in autism spectrum disorder (ASD) and may affect its identification, diagnosis, intervention, and other medical practices in the future. Although previous studies have used bibliometric techniques to analyze and investigate AI, there has been little research on the adoption of AI in ASD. This study aimed to explore the broad applications and research frontiers of AI used in ASD.

Methods

Citation data were retrieved from the Web of Science Core Collection (WoSCC) database to assess the extent to which AI is used in ASD. CiteSpace.5.8. R3 and VOSviewer, two online tools for literature metrology analysis, were used to analyze the data.

Results

A total of 776 publications from 291 countries and regions were analyzed; of these, 256 publications were from the United States and 173 publications were from China, and England had the largest centrality of 0.33; Stanford University had the highest H-index of 17; and the largest cluster label of co-cited references was machine learning. In addition, keywords with a high number of occurrences in this field were autism spectrum disorder (295), children (255), classification (156) and diagnosis (77). The burst keywords from 2021 to 2023 were infants and feature selection, and from 2022 to 2023, the burst keyword was corpus callosum.

Conclusion

This research provides a systematic analysis of the literature concerning AI used in ASD, presenting an overall demonstration in this field. In this area, the United States and China have the largest number of publications, England has the greatest influence, and Stanford University is the most influential. In addition, the research on AI used in ASD mostly focuses on classification and diagnosis, and "infants, feature selection, and corpus callosum are at the forefront, providing directions for future research. However, the use of AI technologies to identify ASD will require further research.

An Umbrella Review of the Fusion of fMRI and AI in Autism

The role of functional magnetic resonance imaging (fMRI) is assuming an increasingly central role in autism diagnosis. The integration of Artificial Intelligence (AI) into the realm of applications further contributes to its development. This study's objective is to analyze emerging themes in this domain through an umbrella review, encompassing systematic reviews. The research methodology was based on a structured process for conducting a literature narrative review, using an umbrella review in PubMed and Scopus. Rigorous criteria, a standard checklist, and a qualification process were meticulously applied. The findings include 20 systematic reviews that underscore key themes in autism research, particularly emphasizing the significance of technological integration, including the pivotal roles of fMRI and AI. This study also highlights the enigmatic role of oxytocin. While acknowledging the immense potential in this field, the outcome does not evade acknowledging the significant challenges and limitations. Intriguingly, there is a growing emphasis on research and innovation in AI, whereas aspects related to the integration of healthcare processes, such as regulation, acceptance, informed consent, and data security, receive comparatively less attention. Additionally, the integration of these findings into Personalized Medicine (PM) represents a promising yet relatively unexplored area within autism research. This study concludes by encouraging scholars to focus on the critical themes of health domain integration, vital for the routine implementation of these applications.

Measuring Engagement in Robot-Assisted Therapy for Autistic Children

Children with autism face a range of challenges when it comes to verbal and nonverbal communication. It is essential that children participate in a variety of social, educational, and therapeutic activities to acquire knowledge that is essential for cognitive and social development. Recent studies have shown that children with autism may be interested in playing with an interactive robot. The robot can engage these children in ways that demonstrate and train essential aspects of human interaction, guiding them in therapeutic sessions to practice more complex forms of interaction found in social human-to-human interactions. This study sets out to investigate Robot-Assisted Autism Therapy (RAAT) and the use of artificial intelligence (AI) approaches for measuring the engagement of children during therapy sessions. The study population consisted of five native Arabic-speaking autistic children aged between 4 and 11 years old. The child-robot interaction was recorded by the robot camera and later used for analysis to detect engagement. The results show that the proposed system offers some accuracy in measuring the engagement of children with ASD. Our findings revealed that robot-assisted therapy is a promising field of application for intelligent social robots, especially to support autistic children in achieving their therapeutic and educational objectives.

Assessing the Potential of Robotics Technology for Enhancing Educational for Children with Autism Spectrum Disorder

Robotics technology has been increasingly used as an educational and intervention tool for children with autism spectrum disorder (ASD). However, there remain research issues and challenges that need to be addressed to fully realize the potential benefits of robot-assisted therapy. This systematic review categorizes and summarizes the literature related to robot educational/training interventions and provides a conceptual framework for collecting and classifying these articles. The challenges identified in this review are classified into four levels: robot-level, algorithm-level, experimental-research-level, and application-level challenges. The review highlights possible future research directions and offers crucial insights for researchers interested in using robots in therapy. The most relevant findings suggest that robot-assisted therapy has the potential to improve social interaction, communication, and emotional regulation skills in children with ASD. Addressing these challenges and seeking new research avenues will be critical to advancing the field of robot-assisted therapy and improving outcomes for children with ASD. This study serves as a roadmap for future research in this important area.

Putting Cats on the Spectrum: A Scoping Review of the Role of Cats in Therapy and Companionship for Autistic Adults and Children

This scoping review brings together existing studies on the use of cats in animal-assisted interventions, as assistance animals and as companion animals for autistic people. A systematic search across PubMed, CINAHL and Scopus in September 2022 identified 13 articles from 12 studies meeting the selection criteria with analysis revealing two key findings, cat-assisted therapeutic interventions, and cats as companion animals. There were five themes that emerged: the characteristics and behaviours of cats that make them suitable for inclusion in homes with autistic people; the bond between the cat and the autistic person; the use of cats as human-substitutes; the multiple ways in which cats improved the lives and social functioning of autistic people; and, some noted drawbacks or considerations of cat ownership. The review generates a comprehensive knowledge base upon which to promote feline therapy in autism and to advocate for further targeted research.

Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors in Social Robot Interactions

Children with autism face challenges in various skills (e.g., communication and social) and they exhibit challenging behaviours. These challenging behaviours represent a challenge to their families, therapists, and caregivers, especially during therapy sessions. In this study, we have investigated several machine learning techniques and data modalities acquired using wearable sensors from children with autism during their interactions with social robots and toys in their potential to detect challenging behaviours. Each child wore a wearable device that collected data. Video annotations of the sessions were used to identify the occurrence of challenging behaviours. Extracted time features (i.e., mean, standard deviation, min, and max) in conjunction with four machine learning techniques were considered to detect challenging behaviors. The heart rate variability (HRV) changes have also been investigated in this study. The XGBoost algorithm has achieved the best performance (i.e., an accuracy of 99%). Additionally, physiological features outperformed the kinetic ones, with the heart rate being the main contributing feature in the prediction performance. One HRV parameter (i.e., RMSSD) was found to correlate with the occurrence of challenging behaviours. This work highlights the importance of developing the tools and methods to detect challenging behaviors among children with autism during aided sessions with social robots.

Artificial scaffolding: Augmenting social cognition by means of robot technology

The concept of scaffolding refers to the support that the environment provides in the acquisition and consolidation of new abilities. Technological advancements allow for support in the acquisition of cognitive capabilities, such as second language acquisition using simple smartphone applications There is, however, one domain of cognition that has been scarcely addressed in the context of technologically assisted scaffolding: social cognition. We explored the possibility of supporting the acquisition of social competencies of a group of children with autism spectrum disorder engaged in a rehabilitation program (age = 5.8 ± 1.14, 10 females, 33 males) by designing two robot-assisted training protocols tailored to Theory of Mind competencies. One protocol was performed with a humanoid robot and the other (control) with a non-anthropomorphic robot. We analyzed changes in NEPSY-II scores before and after the training using mixed effects models. Our results showed that activities with the humanoid significantly improved NEPSY-II scores on the ToM scale. We claim that the motor repertoire of humanoids makes them ideal platforms for artificial scaffolding of social skills in individuals with autism, as they can evoke similar social mechanisms to those elicited in human-human interaction, without providing the same social pressure that another human might exert.

Assistive Robots for Healthcare and Human-Robot Interaction

Assistive robots are still mostly prototypes that only remotely recall human interactive dynamics [...].

Assistive technology for adults on the autism spectrum: A systematic survey

While the needs and care for children on the autism spectrum have been widely investigated, the intervention and services available to autistic adults have been overlooked for a long time. This survey paper reviewed 32 articles that described and evaluated assistive technologies that have been developed and evaluated through a complete circle of interactive product design from ideation, prototype, and user evaluation. These assistive technologies aim to improve independence and living quality in autistic adults. We extracted information from the perspective of requirement gathering, technology designing, and effectiveness of evaluation in the design cycle. We found a general lack of requirements-driven design, and the evaluation process was not standardized either. The lack of requirement gathering results in designs purely based on existing literature without targeting actual user needs. Our synthesis of included paper contributes to developing iterative design considerations in assistive technologies for autistic adults. We also suggest that assistive technologies for autistic adults shift some attention from assisting only autistic adults who require at least substantial support to embracing also those who have been living independently but rather have difficulties in social interaction. Assistive technologies for them have the potentials to help them consolidate and enhance their experiences in independent living.

Fully robotic social environment for teaching and practicing affective interaction: Case of teaching emotion recognition skills to children with autism spectrum disorder, a pilot study

21st century brought along a considerable decrease in social interactions, due to the newly emerged lifestyle around the world, which became more noticeable recently of the COVID-19 pandemic. On the other hand, children with autism spectrum disorder have further complications regarding their social interactions with other humans. In this paper, a fully Robotic Social Environment (RSE), designed to simulate the needed social environment for children, especially those with autism is described. An RSE can be used to simulate many social situations, such as affective interpersonal interactions, in which observational learning can take place. In order to investigate the effectiveness of the proposed RSE, it has been tested on a group of children with autism, who had difficulties in emotion recognition, which in turn, can influence social interaction. An A-B-A single case study was designed to show how RSE can help children with autism recognize four basic facial expressions, i.e., happiness, sadness, anger, and fear, through observing the social interactions of two robots speaking about these facial expressions. The results showed that the emotion recognition skills of the participating children were improved. Furthermore, the results showed that the children could maintain and generalize their emotion recognition skills after the intervention period. In conclusion, the study shows that the proposed RSE, along with other rehabilitation methods, can be effective in improving the emotion recognition skills of children with autism and preparing them to enter human social environments.

Soziale Roboter im Schweizer Gesundheitswesen – Einsatzmöglichkeiten, Chancen und Risiken aus der Sicht von potenziellen Anwendergruppen

Dieser Beitrag der Zeitschrift Gruppe. Interaktion. Organisation. (GIO) berichtet und vertieft die Ergebnisse eines interprofessionellen Projektes im Auftrag der TA-SWISS (Stiftung für Technologiefolgen-Abschätzung). In dem Projekt wurde u. a. untersucht, wie soziale Roboter aus der Sicht von Gesundheitsfachpersonen und von Bewohnerinnen und Bewohnern eines Alterszentrums zukünftig in der Schweiz eingesetzt werden können und welche Chancen und Risiken sie bei diesem Einsatz sehen. Hintergrund dieser Fragestellung war, dass soziale Roboter zunehmend im Gesundheitsbereich eingesetzt werden, die Perspektiven der potenziellen Anwenderinnen und Anwender jedoch nur wenig bekannt sind. Daher wurde mit einem explorativen Studiendesign im August 2020 ein Workshop („Round Table Gesundheit“) mit 26 Teilnehmenden durchgeführt, der Roboterszenarien, vier Fokusgruppeninterviews und eine Nachbefragung beinhaltete. Es zeigte sich in der vertieften Analyse, dass sich die von den Teilnehmenden genannten Einsatzmöglichkeiten von sozialen Robotern einerseits in zwei Anwendergruppen („Patientinnen/Patienten“ und „Gesundheitsfachpersonen“) und andererseits in zwei Rollen des sozialen Roboters (persönlich zugeordnet – „persönlicher Buddy/Assistent“ und nicht persönlich zugeordnet – „hilfreicher Kollege“) einteilen liessen. Die Chancen und Risiken sozialer Roboter liessen sich in die drei Spannungsfelder „Selbstbestimmung vs. soziale Isolation“, „Entlastung vs. Belastung & Abhängigkeit“ und „Sicherheit vs. Gefahren“ kategorisieren. Von potenziellen Anwenderinnen und Anwendern werden somit vielfältige Einsatzmöglichkeiten und Chancen für soziale Roboter im Gesundheitsbereich gesehen. Gleichzeitig gilt es auch die Risiken zu berücksichtigen und zu minimieren, damit soziale Roboter zukünftig erfolgreich in der Praxis eingesetzt werden können.

Understanding Emotions in Children with Developmental Disabilities during Robot Therapy Using EDA

Recent technological advancements have led to the emergence of supportive robotics to help children with developmental disabilities become independent. In conventional research, in robot therapy, experiments are often conducted by operating the robot out of the subject's sight. In this paper, robot therapy using a system that can autonomously recognize the emotions of a child with developmental disabilities and provide feedback was developed. The aim was to quantitatively infer emotional changes in children using skin conductance (EDA) during robot therapy. It was demonstrated that the robot could recognize emotions autonomously and provide feedback to the subjects. Additionally, a quantitative evaluation was conducted using EDA. By analyzing the symptoms related to developmental disorders, it may be possible to improve the recognition rate and tailor therapy based on symptoms.

Telepresence Social Robotics towards Co-Presence: A Review

Telepresence robots are becoming popular in social interactions involving health care, elderly assistance, guidance, or office meetings. There are two types of human psychological experiences to consider in robot-mediated interactions: (1) telepresence, in which a user develops a sense of being present near the remote interlocutor, and (2) co-presence, in which a user perceives the other person as being present locally with him or her. This work presents a literature review on developments supporting robotic social interactions, contributing to improving the sense of presence and co-presence via robot mediation. This survey aims to define social presence, co-presence, identify autonomous “user-adaptive systems” for social robots, and propose a taxonomy for “co-presence” mechanisms. It presents an overview of social robotics systems, applications areas, and technical methods and provides directions for telepresence and co-presence robot design given the actual and future challenges. Finally, we suggest evaluation guidelines for these systems, having as reference face-to-face interaction.

Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness

This paper shows the structure of a mechanical system with 9 DOFs for driving robot eyes, as well as the system's ability to produce facial expressions. It consists of three subsystems which enable the motion of the eyeballs, eyelids, and eyebrows independently to the rest of the face. Due to its structure, the mechanical system of the eyeballs is able to reproduce all of the motions human eyes are capable of, which is an important condition for the realization of binocular function of the artificial robot eyes, as well as stereovision. From a kinematic standpoint, the mechanical systems of the eyeballs, eyelids, and eyebrows are highly capable of generating the movements of the human eye. The structure of a control system is proposed with the goal of realizing the desired motion of the output links of the mechanical systems. The success of the mechanical system is also rated on how well it enables the robot to generate non-verbal emotional content, which is why an experiment was conducted. Due to this, the face of the human-like robot MARKO was used, covered with a face mask to aid in focusing the participants on the eye region. The participants evaluated the efficiency of the robot's non-verbal communication, with certain emotions achieving a high rate of recognition.