Social Robots for Joint Attention Development in Autism Spectrum Disorder: A Systematic Review

Sani-Bozkurt, Sunagül; Bozkuş-Genç, Gülden

doi:10.1080/1034912x.2021.1905153

Cited by 13 publications

(4 citation statements)

References 52 publications

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“…Our review provides an overview of general characteristics, methods, research focus, findings, and the reported gaps and challenges when social robots are used in early developmental research. Previous systematic reviews and scoping reviews have focused on using social robots with older children in other settings, such as in education (97), supporting autism development (98)(99)(100)(101)(102), or various health care contexts (103)(104)(105)(106). Although we maintained the wide approach of a scoping review, we found that an overarching research focus in the reviewed literature was to determine if social robots can act as social partners for young children.…”

Section: Discussionmentioning

confidence: 99%

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

Flatebø,

Tran,

Wang

et al. 2024

Preprint

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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 to 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.

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Section: Discussionmentioning

confidence: 99%

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

Flatebø,

Tran,

Wang

et al. 2024

Preprint

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“…Claiming an embodiment of social robots has an advantage of physical presence over screen based tools while social robots have also been used for head movement analysis, specially in therapeutic interventions [10,11]. The joint attention of a child with a robot was evaluated in [10], by quantifying yaw, pitch and head movement clusters, they established that children with ASD show less response for joint attention and they employ higher energy for head movement.…”

Section: Introductionmentioning

confidence: 99%

Automated Anomalous Child Repetitive Head Movement Identification through Transformer Networks

Wedasingha

Samarasinghe

Seneviratne

et al. 2023

Preprint

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The exponential growth of behavioral disorders among human beings is an increasing concern in the medical community due to a lack of medical resources for early identification of atypical behaviors. Many psychological journals which address behavioral disorders indicate that the most prominent way of puzzling out this problem is to identify behavioral disorder characteristics such as repetitive behaviors in early childhood, and recover through therapy. Even though there are many standards presently used in diagnosing behavioral disorder characteristics, due to a lack of facilities and limited number of professionals in the relevant fields, these traditional standards have failed to cater the increasing number of cases with behavioral disorders. Hence, the need for developing automated approaches to overcome the problems in current systems of diagnosing children with behavioral disorders has arisen from the research community. Therefore, the purpose of this study is to develop an automated model that analyzes a video to distinguish typical, and atypical repetitive head movements of children while using different learning methods to mitigate issues that affect the performance of the model due to the scarcity of child datasets. In this work, we present a fusion of transformer networks, and Non-deterministic Finite Automata (NFA) techniques, which classify repetitive head movements of a child as typical or atypical based on the analysis of gender, age, the type of the repetitive head movement along with count, duration, and frequency of each repetitive head movement. Different transfer learning methods were experimented to enhance the performance of the model. The experimental results on five datasets: NIR face dataset, Bosphorus 3D face dataset, ASD Dataset, SSBD dataset, and head movements in the wild dataset, corroborate our proposed model has outperformed many state-of-the-art frameworks when distinguishing typical and atypical repetitive head movements of children.

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“…In the case of joint attention there is a disparity because there are studies that confirm its effectiveness and others that advise against it. In the work of Sani-Bozkurt and Bozkus-Genc (2021), 13 documents from the period 1990–2020 were reviewed. The aim of the paper was to review recent studies that have been developed with robotic applications for the development of joint attention skills in autistic children.…”

Section: Introductionmentioning

confidence: 99%

Creation of social interaction environments with robot for autistic children: analysis of assessment instruments and type of activities

Lorenzo,

López-Núñez,

Lorenzo-Lledó

et al. 2023

JET

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PurposeThe aim of the study is to conduct a thematic review of assessment tools and types of activities in the application of robotics to autistic students during the period 1996–2021 using Web of Science and Scopus. The sample consisted of 119 documents.Design/methodology/approachNowadays, emerging technologies have become increasingly prevalent across various fields of knowledge. In this regard, robotics is being increasingly applied in the educational environment. The characteristics of this tool are the ones that best suit the needs of autistic students.FindingsResults reveal that 16.80% of the studies used automatic measurement systems, whilst 15.96% of the studies used user observation and recording techniques. As for the tasks, 37.80% were focussed on imitation tasks. Amongst the practical implications is the need to include tasks that could be developed collaboratively in the regular classroom.Originality/valueWith this research, it is intended to disseminate in the scientific community what are the characteristics that should have the interaction activities between a robot and autistic students. In addition, the type of tool needed to evaluate the improvements in the interaction is proposed.

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Social Robots for Joint Attention Development in Autism Spectrum Disorder: A Systematic Review

Cited by 13 publications

References 52 publications

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

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

Automated Anomalous Child Repetitive Head Movement Identification through Transformer Networks

Creation of social interaction environments with robot for autistic children: analysis of assessment instruments and type of activities

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