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Benedicto-Rodríguez G, Bosch F, Juan CG, Bonomini MP, Fernández-Caballero A, Fernandez-Jover E, Ferrández-Vicente JM. Understanding Robot Gesture Perception in Children with Autism Spectrum Disorder during Human-Robot Interaction. Int J Neural Syst 2025:2550026. [PMID: 40231328 DOI: 10.1142/s0129065725500261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2025]
Abstract
Social robots are increasingly being used in therapeutic contexts, especially as a complement in the therapy of children with Autism Spectrum Disorder (ASD). Because of this, the aim of this study is to understand how children with ASD perceive and interpret the gestures made by the robot Pepper versus human instructor, which can also be influenced by verbal communication. This study analyzes the impact of both conditions (verbal and nonverbal communication) and types of gestures (conversational and emotional) on gesture recognition through the study of the accuracy rate and examines the physiological responses of children with the Empatica E4 device. The results reveal that verbal communication is more accessible to children with ASD and neurotypicals (NT), with emotional gestures being more interpretable than conversational gestures. The Pepper robot was found to generate lower responses of emotional arousal compared to the human instructor in both ASD and neurotypical children. This study highlights the potential of robots like Pepper to support the communication skills of children with ASD, especially in structured and predictable nonverbal gestures. However, the findings also point to challenges, such as the need for more reliable robotic communication methods, and highlight the importance of changing interventions tailored to individual needs.
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Affiliation(s)
| | - Facundo Bosch
- Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina
| | - Carlos G Juan
- Universidad Politécnica de Cartagena, Murcia 30202, Spain
- Universidad Miguel Hernández de Elche, Instituto de Bioingeniería, Elche (Alicante) 03202, Spain
| | - Maria Paula Bonomini
- Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina
- Instituto Argentino de Matemática "Alberto P. Calderón" (IAM), CONICET, Buenos Aires, Argentina
| | | | - Eduardo Fernandez-Jover
- CIBER BBN, Universidad Miguel Hernández de Elche, Instituto de Bioingeniería, Elche (Alicante) 03202, Spain
| | - Jose Manuel Ferrández-Vicente
- Universidad Politécnica de Cartagena, Murcia 30202, Spain
- ECTLab[Formula: see text], European University of Technology, Spain
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Shu L, Barradas VR, Qin Z, Koike Y. Facial expression recognition through muscle synergies and estimation of facial keypoint displacements through a skin-musculoskeletal model using facial sEMG signals. Front Bioeng Biotechnol 2025; 13:1490919. [PMID: 40013307 PMCID: PMC11861201 DOI: 10.3389/fbioe.2025.1490919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Accepted: 01/20/2025] [Indexed: 02/28/2025] Open
Abstract
The development of facial expression recognition (FER) and facial expression generation (FEG) systems is essential to enhance human-robot interactions (HRI). The facial action coding system is widely used in FER and FEG tasks, as it offers a framework to relate the action of facial muscles and the resulting facial motions to the execution of facial expressions. However, most FER and FEG studies are based on measuring and analyzing facial motions, leaving the facial muscle component relatively unexplored. This study introduces a novel framework using surface electromyography (sEMG) signals from facial muscles to recognize facial expressions and estimate the displacement of facial keypoints during the execution of the expressions. For the facial expression recognition task, we studied the coordination patterns of seven muscles, expressed as three muscle synergies extracted through non-negative matrix factorization, during the execution of six basic facial expressions. Muscle synergies are groups of muscles that show coordinated patterns of activity, as measured by their sEMG signals, and are hypothesized to form the building blocks of human motor control. We then trained two classifiers for the facial expressions based on extracted features from the sEMG signals and the synergy activation coefficients of the extracted muscle synergies, respectively. The accuracy of both classifiers outperformed other systems that use sEMG to classify facial expressions, although the synergy-based classifier performed marginally worse than the sEMG-based one (classification accuracy: synergy-based 97.4%, sEMG-based 99.2%). However, the extracted muscle synergies revealed common coordination patterns between different facial expressions, allowing a low-dimensional quantitative visualization of the muscle control strategies involved in human facial expression generation. We also developed a skin-musculoskeletal model enhanced by linear regression (SMSM-LRM) to estimate the displacement of facial keypoints during the execution of a facial expression based on sEMG signals. Our proposed approach achieved a relatively high fidelity in estimating these displacements (NRMSE 0.067). We propose that the identified muscle synergies could be used in combination with the SMSM-LRM model to generate motor commands and trajectories for desired facial displacements, potentially enabling the generation of more natural facial expressions in social robotics and virtual reality.
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Affiliation(s)
- Lun Shu
- Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan
| | - Victor R. Barradas
- Institute of Integrated Research, Institute of Science Tokyo, Yokohama, Japan
| | - Zixuan Qin
- Department of Information and Communications Engineering, Institute of Science Tokyo, Yokohama, Japan
| | - Yasuharu Koike
- Institute of Integrated Research, Institute of Science Tokyo, Yokohama, Japan
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Dubois-Sage M, Jacquet B, Jamet F, Baratgin J. People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and Limits. Behav Sci (Basel) 2024; 14:131. [PMID: 38392485 PMCID: PMC10886012 DOI: 10.3390/bs14020131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/02/2024] [Accepted: 02/04/2024] [Indexed: 02/24/2024] Open
Abstract
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.
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Affiliation(s)
- Marion Dubois-Sage
- Laboratoire Cognitions Humaine et Artificielle, RNSR 200515259U, UFR de Psychologie, Université Paris 8, 93526 Saint-Denis, France; (M.D.-S.); (B.J.); (F.J.)
| | - Baptiste Jacquet
- Laboratoire Cognitions Humaine et Artificielle, RNSR 200515259U, UFR de Psychologie, Université Paris 8, 93526 Saint-Denis, France; (M.D.-S.); (B.J.); (F.J.)
- Association P-A-R-I-S, 75005 Paris, France
| | - Frank Jamet
- Laboratoire Cognitions Humaine et Artificielle, RNSR 200515259U, UFR de Psychologie, Université Paris 8, 93526 Saint-Denis, France; (M.D.-S.); (B.J.); (F.J.)
- Association P-A-R-I-S, 75005 Paris, France
- UFR d’Éducation, CY Cergy Paris Université, 95000 Cergy-Pontoise, France
| | - Jean Baratgin
- Laboratoire Cognitions Humaine et Artificielle, RNSR 200515259U, UFR de Psychologie, Université Paris 8, 93526 Saint-Denis, France; (M.D.-S.); (B.J.); (F.J.)
- Association P-A-R-I-S, 75005 Paris, France
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Doğan S, Çolak A. Social robots in the instruction of social skills in autism: a comprehensive descriptive analysis of single-case experimental designs. Disabil Rehabil Assist Technol 2024; 19:325-344. [PMID: 35758001 DOI: 10.1080/17483107.2022.2087772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 06/04/2022] [Indexed: 10/17/2022]
Abstract
PURPOSE The rapid technological advances, the traits of individuals with ASD and their interest in technology are promising for the instruction of social skills to individuals with autism spectrum disorder (ASD) using various technological interventions. Robotic interventions are among these. However, although robotics is frequently used with individuals with ASD, there is a limited number of reviews on social skills instruction and methods. The present study aimed to conduct a comprehensive descriptive analysis on single-case experimental designs where social skills were instructed to individuals with ASD and social robots were included as independent variables. MATERIALS AND METHODS Thirteen single-case experimental designs published in peer-reviewed journals in which social skills were taught to individuals with ASD using social robots were reviewed with a comprehensive descriptive analysis based on five categories: (a) key characteristics, (b) methodological characteristics, (c) findings, (d) data analysis, and (e) key parameters in single-case experimental designs. RESULTS Social robots are generally effective in the instruction of social skills. Several social skills (e.g., making eye contact, social interaction, simple greetings) were instructed in the studies. Humanoid robots and NAO were used generally. The study data were predominantly analyzed statistically. There were several problems in research based on the basic parameters in single-case experimental designs. CONCLUSIONS The researches in this study differ in several respects (e.g., results, data analysis, and dependent variable). Thus, there is still a need for several robotics studies in the instruction of social skills. IMPLICATIONS FOR REHABILITATIONThis study will be a guide for teachers who currently use robots in their classrooms but do not know which skills to use in teaching and how to use them functionally, as it shows applied research with robots.The findings of this research will show implementers working with children with ASD that technological tools can be used in rehabilitation environments, and that teachers can take a place in their robots in interventions for children with ASD, giving them a different perspective.It will be seen that the education of children with ASD is not only 1:1 and with humans, but robots can also provide education. In this way, the power of technology in teaching will become clearer. Especially in rehabilitation.Finally, this research will offer new options in teaching especially for teachers who aim at teaching social skills and will give them the opportunity to comprehensively examine the processes of different studies on these subjects.
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Affiliation(s)
- Serap Doğan
- Department of Special Education, Faculty of Education, Gaziantep University, Gaziantep, Turkey
| | - Aysun Çolak
- Department of Special Education, Faculty of Education, Anadolu University, Eskisehir, Turkey
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Li N, Ross R. Invoking and identifying task-oriented interlocutor confusion in human-robot interaction. Front Robot AI 2023; 10:1244381. [PMID: 38054199 PMCID: PMC10694506 DOI: 10.3389/frobt.2023.1244381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/31/2023] [Indexed: 12/07/2023] Open
Abstract
Successful conversational interaction with a social robot requires not only an assessment of a user's contribution to an interaction, but also awareness of their emotional and attitudinal states as the interaction unfolds. To this end, our research aims to systematically trigger, but then interpret human behaviors to track different states of potential user confusion in interaction so that systems can be primed to adjust their policies in light of users entering confusion states. In this paper, we present a detailed human-robot interaction study to prompt, investigate, and eventually detect confusion states in users. The study itself employs a Wizard-of-Oz (WoZ) style design with a Pepper robot to prompt confusion states for task-oriented dialogues in a well-defined manner. The data collected from 81 participants includes audio and visual data, from both the robot's perspective and the environment, as well as participant survey data. From these data, we evaluated the correlations of induced confusion conditions with multimodal data, including eye gaze estimation, head pose estimation, facial emotion detection, silence duration time, and user speech analysis-including emotion and pitch analysis. Analysis shows significant differences of participants' behaviors in states of confusion based on these signals, as well as a strong correlation between confusion conditions and participants own self-reported confusion scores. The paper establishes strong correlations between confusion levels and these observable features, and lays the ground or a more complete social and affect oriented strategy for task-oriented human-robot interaction. The contributions of this paper include the methodology applied, dataset, and our systematic analysis.
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Affiliation(s)
- Na Li
- School of Computer Science, Technological University, Dublin, Ireland
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Bertacchini F, Demarco F, Scuro C, Pantano P, Bilotta E. A social robot connected with chatGPT to improve cognitive functioning in ASD subjects. Front Psychol 2023; 14:1232177. [PMID: 37868599 PMCID: PMC10585023 DOI: 10.3389/fpsyg.2023.1232177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/11/2023] [Indexed: 10/24/2023] Open
Abstract
Neurodevelopmental Disorders (NDDs) represent a significant healthcare and economic burden for families and society. Technology, including AI and digital technologies, offers potential solutions for the assessment, monitoring, and treatment of NDDs. However, further research is needed to determine the effectiveness, feasibility, and acceptability of these technologies in NDDs, and to address the challenges associated with their implementation. In this work, we present the application of social robotics using a Pepper robot connected to the OpenAI system (Chat-GPT) for real-time dialogue initiation with the robot. After describing the general architecture of the system, we present two possible simulated interaction scenarios of a subject with Autism Spectrum Disorder in two different situations. Limitations and future implementations are also provided to provide an overview of the potential developments of interconnected systems that could greatly contribute to technological advancements for Neurodevelopmental Disorders (NDD).
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Affiliation(s)
- Francesca Bertacchini
- Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende, Italy
- Laboratory of Cognitive Psychology and Mathematical Modelling, University of Calabria, Rende, Italy
| | - Francesco Demarco
- Laboratory of Cognitive Psychology and Mathematical Modelling, University of Calabria, Rende, Italy
- Department of Physics, University of Calabria, Rende, Italy
| | - Carmelo Scuro
- Laboratory of Cognitive Psychology and Mathematical Modelling, University of Calabria, Rende, Italy
- Department of Physics, University of Calabria, Rende, Italy
| | - Pietro Pantano
- Laboratory of Cognitive Psychology and Mathematical Modelling, University of Calabria, Rende, Italy
- Department of Physics, University of Calabria, Rende, Italy
| | - Eleonora Bilotta
- Laboratory of Cognitive Psychology and Mathematical Modelling, University of Calabria, Rende, Italy
- Department of Physics, University of Calabria, Rende, Italy
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Yan T, Lin S, Wang J, Deng F, Jiang Z, Chen G, Su J, Zhang J. AppraisalCloudPCT: A Computational Model of Emotions for Socially Interactive Robots for Autistic Rehabilitation. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2023; 2023:5960764. [PMID: 36926186 PMCID: PMC10014163 DOI: 10.1155/2023/5960764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/13/2022] [Accepted: 01/21/2023] [Indexed: 03/09/2023]
Abstract
Computational models of emotions can not only improve the effectiveness and efficiency of human-robot interaction but also coordinate a robot to adapt to its environment better. When designing computational models of emotions for socially interactive robots, especially for robots for people with special needs such as autistic children, one should take into account the social and communicative characteristics of such groups of people. This article presents a novel computational model of emotions called AppraisalCloudPCT that is suitable for socially interactive robots that can be adopted in autistic rehabilitation which, to the best of our knowledge, is the first computational model of emotions built for robots that can satisfy the needs of a special group of people such as autistic children. To begin with, some fundamental and notable computational models of emotions (e.g., OCC, Scherer's appraisal theory, PAD) that have deep and profound influence on building some significant models (e.g., PRESENCE, iGrace, xEmotion) for socially interactive robots are revisited. Then, a comparative assessment between our AppraisalCloudPCT and other five significant models for socially interactive robots is conducted. Great efforts have been made in building our proposed model to meet all of the six criteria for comparison, by adopting the appraisal theories on emotions, perceptual control theory on emotions, a component model view of appraisal models, and cloud robotics. Details of how to implement our model in a socially interactive robot we developed for autistic rehabilitation are also elaborated in this article. Future studies should examine how our model performs in different robots and also in more interactive scenarios.
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Affiliation(s)
- Ting Yan
- The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
| | - Shengzhao Lin
- Institute of Robotics and Intelligent Manufacturing, the Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong 518172, China
| | - Jinfeng Wang
- Department of Mathematical Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Fuhao Deng
- Shenzhen TOP Intelligent Manufacturing and Technology Co., Ltd., Shenzhen, Guangdong 518129, China
| | - Zijian Jiang
- Shenzhen TOP Intelligent Manufacturing and Technology Co., Ltd., Shenzhen, Guangdong 518129, China
| | - Gong Chen
- Sunwoda Electronic Co., Ltd., Shiyan Street, Bao'an District, Shenzhen 518000, China
| | - Jionglong Su
- School of AI and Advanced Computing, XJTLU Entrepreneur College (Taicang), Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Jiaming Zhang
- Institute of Robotics and Intelligent Manufacturing, the Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong 518172, China
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Soleiman P, Moradi H, Mehralizadeh B, Ameri H, Arriaga RI, Pouretemad HR, Baghbanzadeh N, Vahid LK. 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. Front Robot AI 2023; 10:1088582. [PMID: 37207048 PMCID: PMC10190599 DOI: 10.3389/frobt.2023.1088582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 04/03/2023] [Indexed: 05/21/2023] Open
Abstract
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.
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Affiliation(s)
| | - Hadi Moradi
- School of ECE, University of Tehran, Tehran, Iran
- Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Republic of Korea
- *Correspondence: Hadi Moradi,
| | | | - Hamed Ameri
- Department of Psychology, University of Tehran, Tehran, Iran
| | - Rosa I. Arriaga
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States
| | | | | | - Leila Kashani Vahid
- Department of Psychology, Islamic Azad University Science and Research Branch, Tehran, Iran
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9
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Exploring smart retailing: anthropomorphism in voice shopping of smart speaker. INFORMATION TECHNOLOGY & PEOPLE 2022. [DOI: 10.1108/itp-07-2021-0536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
PurposeThe purpose of this paper is to investigate the effects of anthropomorphism and identify factors related to adopting voice shopping on smart speakers.Design/methodology/approachProgress in partial least squares structural equation modeling (PLS-SEM) approach is used to test the proposed research framework regarding anthropomorphism and user perceptions on voice shopping via smart speakers. Individuals' responses to questions about attitude and intention to use voice shopping via smart speakers were collected and analyzed.FindingsThe results showed that anthropomorphism had a positive influence on satisfaction, which, in turn, had a positive impact on intention to adopt voice shopping, and customers had positive opinions regarding smart speakers.Research limitations/implicationsThis study only reflects a younger perspective on smart speaker voice shopping. This study identified the characteristics of smart speakers that increase customers' intention to purchase, which can be used to formulate sales strategies and management guidelines.Practical implicationsThis research provided a new perspective to enable practitioners to promote smart speakers for voice shopping. Smart speaker manufacturers can utilize the findings of this research to improve the system design of smart speakers to further facilitate voice shopping.Originality/valueUnlike previous studies, which focused on product attributes of smart speakers or voice shopping experiences, this study provided a clear picture of how the anthropomorphic feature of smart speakers affects customers' intention to adopt voice shopping.
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Bharatharaj J, Sasthan Kutty SK, Munisamy A, Krägeloh CU. What do Members of Parliament in India Think of Robots? Validation of the Frankenstein Syndrome Questionnaire and Comparison with Other Population Groups. Int J Soc Robot 2022. [DOI: 10.1007/s12369-022-00921-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
AbstractIndia is the second largest country in the world in terms of population and thus a considerable market for potential future robot applications as well as a location for manufacturing and production. While work has started to explore attitudes towards robots, very little is known about the perceptions of robots in India, particularly of political leaders who have the ability to effect rapid change. The present study administered the 30-item Frankenstein Syndrome Questionnaire to 31 Lok Sabha (Lower House) and Rajya Sabah (Upper House) members of the Indian Parliament (MPs) as well as doctors (n = 94), medical students (n = 493), and engineering students (n = 1104) for comparative purposes. Because no information had been available about the psychometric properties of the scale for use in India, a prior Rasch analysis explored the suitability of the commonly used five-factor model. The five subscales did not possess sufficient reliability, and a more psychometrically robust 26-item two-factor model (positive and negative attitudes) was utilized instead. The results revealed a higher degree of positive attitudes in MPs and doctors as compared to the two student groups. Negative attitudes, on the other hand, were strongest in doctors, followed by students. MPs had significantly less negative views compared to all other comparison groups. This study provides valuable insights into attitudes towards robots in India. In general, MPs appear to have more favourable views than comparison groups in India. A slightly shorter and more parsimonious version of the Frankenstein Syndrome Questionnaire has now also been proposed, with improved psychometric properties.
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Cao XJ, Liu XQ. Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges. World J Psychiatry 2022; 12:1287-1297. [PMID: 36389087 PMCID: PMC9641379 DOI: 10.5498/wjp.v12.i10.1287] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/09/2022] [Accepted: 09/22/2022] [Indexed: 02/05/2023] Open
Abstract
Artificial intelligence-based technologies are gradually being applied to psych-iatric research and practice. This paper reviews the primary literature concerning artificial intelligence-assisted psychosis risk screening in adolescents. In terms of the practice of psychosis risk screening, the application of two artificial intelligence-assisted screening methods, chatbot and large-scale social media data analysis, is summarized in detail. Regarding the challenges of psychiatric risk screening, ethical issues constitute the first challenge of psychiatric risk screening through artificial intelligence, which must comply with the four biomedical ethical principles of respect for autonomy, nonmaleficence, beneficence and impartiality such that the development of artificial intelligence can meet the moral and ethical requirements of human beings. By reviewing the pertinent literature concerning current artificial intelligence-assisted adolescent psychosis risk screens, we propose that assuming they meet ethical requirements, there are three directions worth considering in the future development of artificial intelligence-assisted psychosis risk screening in adolescents as follows: nonperceptual real-time artificial intelligence-assisted screening, further reducing the cost of artificial intelligence-assisted screening, and improving the ease of use of artificial intelligence-assisted screening techniques and tools.
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Affiliation(s)
- Xiao-Jie Cao
- Graduate School of Education, Peking University, Beijing 100871, China
| | - Xin-Qiao Liu
- School of Education, Tianjin University, Tianjin 300350, China
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12
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Wang Z, Liu J, Zhang W, Nie W, Liu H. Diagnosis and Intervention for Children With Autism Spectrum Disorder: A Survey. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2021.3093040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Zhiyong Wang
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | - Jingjing Liu
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | - Wanqi Zhang
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Nie
- State Key Laboratory of Robotics and Systems, Harbin Institute of Technology Shenzhen, Shenzhen, China
| | - Honghai Liu
- State Key Laboratory of Robotics and Systems, Harbin Institute of Technology Shenzhen, Shenzhen, China
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13
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Kouroupa A, Laws KR, Irvine K, Mengoni SE, Baird A, Sharma S. The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis. PLoS One 2022; 17:e0269800. [PMID: 35731805 PMCID: PMC9216612 DOI: 10.1371/journal.pone.0269800] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/30/2022] [Indexed: 11/18/2022] Open
Abstract
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).
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Affiliation(s)
- Athanasia Kouroupa
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
- Division of Psychiatry, University College London, London, United Kingdom
| | - Keith R. Laws
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
| | - Karen Irvine
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
| | - Silvana E. Mengoni
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
| | - Alister Baird
- Division of Psychiatry, University College London, London, United Kingdom
| | - Shivani Sharma
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
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14
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The Quantitative Case-by-Case Analyses of the Socio-Emotional Outcomes of Children with ASD in Robot-Assisted Autism Therapy. MULTIMODAL TECHNOLOGIES AND INTERACTION 2022. [DOI: 10.3390/mti6060046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
With its focus on robot-assisted autism therapy, this paper presents case-by-case analyses of socio-emotional outcomes of 34 children aged 3–12 years old, with different cases of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). We grouped children by the following characteristics: ASD alone (n = 22), ASD+ADHD (n = 12), verbal (n = 11), non-verbal (n = 23), low-functioning autism (n = 24), and high-functioning autism (n = 10). This paper provides a series of separate quantitative analyses across the first and last sessions, adaptive and non-adaptive sessions, and parent and no-parent sessions, to present child experiences with the NAO robot, during play-based activities. The results suggest that robots are able to interact with children in social ways and influence their social behaviors over time. Each child with ASD is a unique case and needs an individualized approach to practice and learn social skills with the robot. We, finally, present specific child–robot intricacies that affect how children engage and learn over time as well as across different sessions.
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15
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Parental Influence in Disengagement during Robot-Assisted Activities: A Case Study of a Parent and Child with Autism Spectrum Disorder. MULTIMODAL TECHNOLOGIES AND INTERACTION 2022. [DOI: 10.3390/mti6050039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
We examined the influence of a parent on robot-assisted activities for a child with Autism Spectrum Disorder. We observed the interactions between a robot and the child wearing a wearable device during free play sessions. The child participated in four sessions with the parent and interacted willingly with the robot, therapist, and parent. The parent intervened when the child did not interact with the robot, considered “disengagement with the robot”. The number and method of intervention were decided solely by the parent. This study adopted video recording for behavioral observations and specifically observed the situations before the disengagement with the robot, the child’s behaviors during disengagement, and the parent’s intervention. The results showed that mostly the child abruptly discontinued the interactions with the robot without being stimulated by the surrounding environment. The second most common reason was being distracted by various devices in the play sessions, such as the wearable device, a video camera, and a laptop. Once he was disengaged with the robot, he primarily exhibited inappropriate and repetitive behaviors accentuating the symptoms of autism spectrum disorder. The child could re-initiate the interaction with the robot with an 80% chance through the parent’s intervention. This suggests that engagement with a robot may differ depending on the parent’s participation. Moreover, we must consider types of parental feedback to re-initiate engagement with a robot to benefit from the therapy adequately. In addition, environmental distractions must be considered, especially when using multiple devices for therapy.
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16
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Burns RB, Lee H, Seifi H, Faulkner R, Kuchenbecker KJ. Endowing a NAO Robot With Practical Social-Touch Perception. Front Robot AI 2022; 9:840335. [PMID: 35516789 PMCID: PMC9061995 DOI: 10.3389/frobt.2022.840335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/16/2022] [Indexed: 11/14/2022] Open
Abstract
Social touch is essential to everyday interactions, but current socially assistive robots have limited touch-perception capabilities. Rather than build entirely new robotic systems, we propose to augment existing rigid-bodied robots with an external touch-perception system. This practical approach can enable researchers and caregivers to continue to use robotic technology they have already purchased and learned about, but with a myriad of new social-touch interactions possible. This paper presents a low-cost, easy-to-build, soft tactile-perception system that we created for the NAO robot, as well as participants’ feedback on touching this system. We installed four of our fabric-and-foam-based resistive sensors on the curved surfaces of a NAO’s left arm, including its hand, lower arm, upper arm, and shoulder. Fifteen adults then performed five types of affective touch-communication gestures (hitting, poking, squeezing, stroking, and tickling) at two force intensities (gentle and energetic) on the four sensor locations; we share this dataset of four time-varying resistances, our sensor patterns, and a characterization of the sensors’ physical performance. After training, a gesture-classification algorithm based on a random forest identified the correct combined touch gesture and force intensity on windows of held-out test data with an average accuracy of 74.1%, which is more than eight times better than chance. Participants rated the sensor-equipped arm as pleasant to touch and liked the robot’s presence significantly more after touch interactions. Our promising results show that this type of tactile-perception system can detect necessary social-touch communication cues from users, can be tailored to a variety of robot body parts, and can provide HRI researchers with the tools needed to implement social touch in their own systems.
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Affiliation(s)
- Rachael Bevill Burns
- Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany
| | - Hyosang Lee
- Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.,Department of Electrical Engineering, Institute of Smart Sensors, University of Stuttgart, Stuttgart, Germany
| | - Hasti Seifi
- Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.,Department of Computer Science, Human-Centred Computing, University of Copenhagen, Copenhagen, Denmark
| | - Robert Faulkner
- Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany
| | - Katherine J Kuchenbecker
- Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany
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17
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Baraka K, Couto M, Melo FS, Paiva A, Veloso M. “Sequencing Matters”: Investigating Suitable Action Sequences in Robot-Assisted Autism Therapy. Front Robot AI 2022; 9:784249. [PMID: 35356059 PMCID: PMC8959535 DOI: 10.3389/frobt.2022.784249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 02/11/2022] [Indexed: 11/13/2022] Open
Abstract
Social robots have been shown to be promising tools for delivering therapeutic tasks for children with Autism Spectrum Disorder (ASD). However, their efficacy is currently limited by a lack of flexibility of the robot’s social behavior to successfully meet therapeutic and interaction goals. Robot-assisted interventions are often based on structured tasks where the robot sequentially guides the child towards the task goal. Motivated by a need for personalization to accommodate a diverse set of children profiles, this paper investigates the effect of different robot action sequences in structured socially interactive tasks targeting attention skills in children with different ASD profiles. Based on an autism diagnostic tool, we devised a robotic prompting scheme on a NAO humanoid robot, aimed at eliciting goal behaviors from the child, and integrated it in a novel interactive storytelling scenario involving screens. We programmed the robot to operate in three different modes: diagnostic-inspired (Assess), personalized therapy-inspired (Therapy), and random (Explore). Our exploratory study with 11 young children with ASD highlights the usefulness and limitations of each mode according to different possible interaction goals, and paves the way towards more complex methods for balancing short-term and long-term goals in personalized robot-assisted therapy.
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Affiliation(s)
- Kim Baraka
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
- Group on AI for People and Society (GAIPS), INESC-ID, Porto Salvo, Portugal
- Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal
- *Correspondence: Kim Baraka,
| | - Marta Couto
- Group on AI for People and Society (GAIPS), INESC-ID, Porto Salvo, Portugal
- Centro de Desenvolvimento da Criança, Hospital Garcia de Orta, Almada, Portugal
| | - Francisco S. Melo
- Group on AI for People and Society (GAIPS), INESC-ID, Porto Salvo, Portugal
- Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal
| | - Ana Paiva
- Group on AI for People and Society (GAIPS), INESC-ID, Porto Salvo, Portugal
- Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal
| | - Manuela Veloso
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
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18
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Demiralay Ş, Keser İ. The effect of pet therapy on the stress and social anxiety levels of disabled children: A randomized controlled trial. Complement Ther Clin Pract 2022; 48:101574. [DOI: 10.1016/j.ctcp.2022.101574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 11/26/2022]
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19
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Pérez-Fuster P, Herrera G, Kossyvaki L, Ferrer A. Enhancing Joint Attention Skills in Children on the Autism Spectrum through an Augmented Reality Technology-Mediated Intervention. CHILDREN (BASEL, SWITZERLAND) 2022; 9:258. [PMID: 35204977 PMCID: PMC8870736 DOI: 10.3390/children9020258] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 01/31/2022] [Accepted: 02/10/2022] [Indexed: 11/16/2022]
Abstract
In the present study, the effects of an intervention based on an augmented reality technology called Pictogram Room were examined. The objective of the intervention was to improve the responding to joint attention (RJA) skills of gaze following and pointing in six children on the autism spectrum between 3 and 8 years old. A multiple baseline single-subject experimental design was conducted for 12 weeks in a school setting. Results indicated that all of the participant children improved performance in RJA following the intervention. Improvements were maintained over time and generalised to real-world situations. These findings demonstrate that autistic children can improve their RJA skills with a targeted and engaging intervention based on an accessible augmented reality technology tool.
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Affiliation(s)
- Patricia Pérez-Fuster
- Department of Educational Psychology and Psychobiology, School of Education, Universidad Internacional de La Rioja, 26006 Logroño, Spain
- Autism and Technologies Laboratory, University Research Institute on Robotics and Information and Communication Technologies (IRTIC), Universitat de València, 46010 Valencia, Spain;
| | - Gerardo Herrera
- Autism and Technologies Laboratory, University Research Institute on Robotics and Information and Communication Technologies (IRTIC), Universitat de València, 46010 Valencia, Spain;
| | - Lila Kossyvaki
- Department of Disability, Inclusion and Special Needs (DISN), School of Education, University of Birmingham, Birmingham B15 2TT, UK;
| | - Antonio Ferrer
- Department of Developmental and Educational Psychology, Faculty of Psychology, Universitat de València, 46010 Valencia, Spain;
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20
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Rasouli S, Gupta G, Nilsen E, Dautenhahn K. Potential Applications of Social Robots in Robot-Assisted Interventions for Social Anxiety. Int J Soc Robot 2022; 14:1-32. [PMID: 35096198 PMCID: PMC8787185 DOI: 10.1007/s12369-021-00851-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/24/2021] [Indexed: 12/31/2022]
Abstract
AbstractSocial anxiety disorder or social phobia is a condition characterized by debilitating fear and avoidance of different social situations. We provide an overview of social anxiety and evidence-based behavioural and cognitive treatment approaches for this condition. However, treatment avoidance and attrition are high in this clinical population, which calls for innovative approaches, including computer-based interventions, that could minimize barriers to treatment and enhance treatment effectiveness. After reviewing existing assistive technologies for mental health interventions, we provide an overview of how social robots have been used in many clinical interventions. We then propose to integrate social robots in conventional behavioural and cognitive therapies for both children and adults who struggle with social anxiety. We categorize the different therapeutic roles that social robots can potentially play in activities rooted in conventional therapies for social anxiety and oriented towards symptom reduction, social skills development, and improvement in overall quality of life. We discuss possible applications of robots in this context through four scenarios. These scenarios are meant as ‘food for thought’ for the research community which we hope will inspire future research. We discuss risks and concerns for using social robots in clinical practice. This article concludes by highlighting the potential advantages as well as limitations of integrating social robots in conventional interventions to improve accessibility and standard of care as well as outlining future steps in relation to this research direction. Clearly recognizing the need for future empirical work in this area, we propose that social robots may be an effective component in robot-assisted interventions for social anxiety, not replacing, but complementing the work of clinicians. We hope that this article will spark new research, and research collaborations in the highly interdisciplinary field of robot-assisted interventions for social anxiety.
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Affiliation(s)
- Samira Rasouli
- Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1 Canada
| | - Garima Gupta
- Department of Psychology, University of Waterloo, Waterloo, Ontario Canada
| | - Elizabeth Nilsen
- Department of Psychology, University of Waterloo, Waterloo, Ontario Canada
| | - Kerstin Dautenhahn
- Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1 Canada
- Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario Canada
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21
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Social robots and therapeutic adherence: A new challenge in pediatric asthma? Paediatr Respir Rev 2021; 40:46-51. [PMID: 33386280 DOI: 10.1016/j.prrv.2020.11.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 11/19/2020] [Accepted: 11/20/2020] [Indexed: 02/06/2023]
Abstract
Social Robots are used in different contexts and, in healthcare, they are better known as Socially Assistive Robots. In the context of asthma, the use of Socially Assistive Robots has the potential to increase motivation and engagement to treatment. Other positive roles proposed for Socially Assistive Robots are to provide education, training regarding treatments, and feedback to patients. This review evaluates emerging interventions for improving treatment adherence in pediatric asthma, focusing on the possible future role of social robots in the clinical practice.
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22
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Amirova A, Rakhymbayeva N, Yadollahi E, Sandygulova A, Johal W. 10 Years of Human-NAO Interaction Research: A Scoping Review. Front Robot AI 2021; 8:744526. [PMID: 34869613 PMCID: PMC8640132 DOI: 10.3389/frobt.2021.744526] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 10/21/2021] [Indexed: 11/30/2022] Open
Abstract
The evolving field of human-robot interaction (HRI) necessitates that we better understand how social robots operate and interact with humans. This scoping review provides an overview of about 300 research works focusing on the use of the NAO robot from 2010 to 2020. This study presents one of the most extensive and inclusive pieces of evidence on the deployment of the humanoid NAO robot and its global reach. Unlike most reviews, we provide both qualitative and quantitative results regarding how NAO is being used and what has been achieved so far. We analyzed a wide range of theoretical, empirical, and technical contributions that provide multidimensional insights, such as general trends in terms of application, the robot capabilities, its input and output modalities of communication, and the human-robot interaction experiments that featured NAO (e.g. number and roles of participants, design, and the length of interaction). Lastly, we derive from the review some research gaps in current state-of-the-art and provide suggestions for the design of the next generation of social robots.
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Affiliation(s)
- Aida Amirova
- Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Nazerke Rakhymbayeva
- Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Elmira Yadollahi
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Anara Sandygulova
- Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Wafa Johal
- University of Melbourne, Melbourne, VIC, Australia
- UNSW, Sydney, NSW, Australia
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23
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Wood LJ, Zaraki A, Robins B, Dautenhahn K. Developing Kaspar: A Humanoid Robot for Children with Autism. Int J Soc Robot 2021; 13:491-508. [PMID: 34721730 PMCID: PMC8550690 DOI: 10.1007/s12369-019-00563-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/17/2019] [Indexed: 11/03/2022]
Abstract
In the late 1990s using robotic technology to assist children with Autistic Spectrum Condition (ASD) emerged as a potentially useful area of research. Since then the field of assistive robotics for children with ASD has grown considerably with many academics trialling different robots and approaches. One such robot is the humanoid robot Kaspar that was originally developed in 2005 and has continually been built upon since, taking advantage of technological developments along the way. A key principle in the development of Kaspar since its creation has been to ensure that all of the advances to the platform are driven by the requirements of the users. In this paper we discuss the development of Kaspar's design and explain the rationale behind each change to the platform. Designing and building a humanoid robot to interact with and help children with ASD is a multidisciplinary challenge that requires knowledge of the mechanical engineering, electrical engineering, Human-Computer Interaction (HCI), Child-Robot Interaction (CRI) and knowledge of ASD. The Kaspar robot has benefited from the wealth of knowledge accrued over years of experience in robot-assisted therapy for children with ASD. By showing the journey of how the Kaspar robot has developed we aim to assist others in the field develop such technologies further.
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Affiliation(s)
- Luke J Wood
- School of Computer Science, University of Hertfordshire, Hatfield, UK
| | - Abolfazl Zaraki
- School of Computer Science, University of Hertfordshire, Hatfield, UK
| | - Ben Robins
- School of Computer Science, University of Hertfordshire, Hatfield, UK
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24
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Robotic Psychology: A PRISMA Systematic Review on Social-Robot-Based Interventions in Psychological Domains. J 2021. [DOI: 10.3390/j4040048] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Current technological advancements have allowed robots to be successfully employed in the healthcare sector. However, the recently acquired ability of social robots to process social information and act according to it has potentially made them very well suited to support or conduct psychological interventions. The present paper carried out a systematic review of the available literature regarding social-robot-based interventions in psychological domains using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The inclusion criteria were: (i) publication date until 2020; (ii) being an empirical study, master thesis, or project report; (iii) written in English or Italian languages (the two languages spoken by the authors); (iv) published in a scholarly peer-reviewed journal or conference proceedings, or were Ph.D. or master’s theses; and (v) assessed “social robot”-based intervention in psychological domains. Overall, the review showed that three main areas may benefit from social-robot-based interventions: social skills, mood, and wellbeing (e.g., stress and anxiety levels). Interestingly, social robots seemed to have a performance comparable to, and sometimes even better than, human operators. The main, but not exclusive, target of robot-based interventions in the psychological field was children with autism spectrum disorder (ASD). As evidence is, however, still limited and in an embryonic state, deeper investigations are needed to assess the full potential of social robots for the purposes of psychological intervention. This is relevant, considering the role that social robots could have in overcoming barriers to access psychological assessment and therapies.
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25
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Aryania A, Aghdasi HS, Heshmati R, Bonarini A. Robust risk-averse multi-armed bandits with application in social engagement behavior of children with autism spectrum disorder while imitating a humanoid robot. Inf Sci (N Y) 2021. [DOI: 10.1016/j.ins.2021.05.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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26
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Abstract
AbstractOver the last two decades, several deployments of robots for in-house assistance of older adults have been trialled. However, these solutions are mostly prototypes and remain unused in real-life scenarios. In this work, we review the historical and current landscape of the field, to try and understand why robots have yet to succeed as personal assistants in daily life. Our analysis focuses on two complementary aspects: the capabilities of the physical platform and the logic of the deployment. The former analysis shows regularities in hardware configurations and functionalities, leading to the definition of a set of six application-level capabilities (exploration, identification, remote control, communication, manipulation, and digital situatedness). The latter focuses on the impact of robots on the daily life of users and categorises the deployment of robots for healthcare interventions using three types of services: support, mitigation, and response. Our investigation reveals that the value of healthcare interventions is limited by a stagnation of functionalities and a disconnection between the robotic platform and the design of the intervention. To address this issue, we propose a novel co-design toolkit, which uses an ecological framework for robot interventions in the healthcare domain. Our approach connects robot capabilities with known geriatric factors, to create a holistic view encompassing both the physical platform and the logic of the deployment. As a case study-based validation, we discuss the use of the toolkit in the pre-design of the robotic platform for an pilot intervention, part of the EU large-scale pilot of the EU H2020 GATEKEEPER project.
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27
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Raptopoulou A, Komnidis A, Bamidis PD, Astaras A. Human-robot interaction for social skill development in children with ASD: A literature review. Healthc Technol Lett 2021; 8:90-96. [PMID: 34295506 PMCID: PMC8284575 DOI: 10.1049/htl2.12013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 12/06/2020] [Accepted: 12/14/2020] [Indexed: 11/25/2022] Open
Abstract
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.
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Affiliation(s)
- Anastasia Raptopoulou
- Lab of Medical PhysicsSchool of MedicineAristotle University of ThessalonikiThessaloniki54124Greece
| | - Antonios Komnidis
- Lab of Medical PhysicsSchool of MedicineAristotle University of ThessalonikiThessaloniki54124Greece
| | - Panagiotis D. Bamidis
- Lab of Medical PhysicsSchool of MedicineAristotle University of ThessalonikiThessaloniki54124Greece
| | - Alexandros Astaras
- Lab of Medical PhysicsSchool of MedicineAristotle University of ThessalonikiThessaloniki54124Greece
- Computer ScienceAmerican College of ThessalonikiThessalonikiGreece
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28
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Abstract
Social robots may become an innovative means to improve the well-being of individuals. Earlier research has shown that people easily self-disclose to a social robot, even in cases where it was unintended by the designers. We report on an experiment considering self-disclosing in a diary journal or to a social robot after negative mood induction. An off-the-shelf robot was complemented with our in-house developed AI chatbot, which could talk about ‘hot topics’ after training it with thousands of entries on a complaint website. We found that people who felt strongly negative after being exposed to shocking video footage benefited the most from talking to our robot, rather than writing down their feelings. For people less affected by the treatment, a confidential robot chat or writing a journal page did not differ significantly. We discuss emotion theory in relation to robotics and possibilities for an application in design (the emoji-enriched ‘talking stress ball’). We also underline the importance of otherwise disregarded outliers in a data set of therapeutic nature.
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29
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Skeleton Driven Action Recognition Using an Image-Based Spatial-Temporal Representation and Convolution Neural Network. SENSORS 2021; 21:s21134342. [PMID: 34201991 PMCID: PMC8271982 DOI: 10.3390/s21134342] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 11/22/2022]
Abstract
Individuals with Autism Spectrum Disorder (ASD) typically present difficulties in engaging and interacting with their peers. Thus, researchers have been developing different technological solutions as support tools for children with ASD. Social robots, one example of these technological solutions, are often unaware of their game partners, preventing the automatic adaptation of their behavior to the user. Information that can be used to enrich this interaction and, consequently, adapt the system behavior is the recognition of different actions of the user by using RGB cameras or/and depth sensors. The present work proposes a method to automatically detect in real-time typical and stereotypical actions of children with ASD by using the Intel RealSense and the Nuitrack SDK to detect and extract the user joint coordinates. The pipeline starts by mapping the temporal and spatial joints dynamics onto a color image-based representation. Usually, the position of the joints in the final image is clustered into groups. In order to verify if the sequence of the joints in the final image representation can influence the model’s performance, two main experiments were conducted where in the first, the order of the grouped joints in the sequence was changed, and in the second, the joints were randomly ordered. In each experiment, statistical methods were used in the analysis. Based on the experiments conducted, it was found statistically significant differences concerning the joints sequence in the image, indicating that the order of the joints might impact the model’s performance. The final model, a Convolutional Neural Network (CNN), trained on the different actions (typical and stereotypical), was used to classify the different patterns of behavior, achieving a mean accuracy of 92.4% ± 0.0% on the test data. The entire pipeline ran on average at 31 FPS.
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30
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Romero-García R, Martínez-Tomás R, Pozo P, de la Paz F, Sarriá E. Q-CHAT-NAO: A robotic approach to autism screening in toddlers. J Biomed Inform 2021; 118:103797. [PMID: 33933653 DOI: 10.1016/j.jbi.2021.103797] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 04/24/2021] [Accepted: 04/26/2021] [Indexed: 10/21/2022]
Abstract
The use of humanoid robots as assistants in therapy processes is not new. Several projects in the past several years have achieved promising results when combining human-robot interaction with standard techniques. Moreover, there are multiple screening systems for autism; one of the most used systems is the Quantitative Checklist for Autism in Toddlers (Q-CHAT-10), which includes ten questions to be answered by the parents or caregivers of a child. We present Q-CHAT-NAO, an observation-based autism screening system supported by a NAO robot. It includes the six questions of the Q-CHAT-10 that can be adapted to work in a robotic context; unlike the original system, it obtains information from the toddler instead of from an indirect source. The detection results obtained after applying machine learning models to the six questions in the Autistic Spectrum Disorder Screening Data for Toddlers dataset were almost equivalent to those of the original version with ten questions. These findings indicate that the Q-CHAT-NAO could be a screening option that would exploit all the benefits related to human-robot interaction.
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Affiliation(s)
- Rubén Romero-García
- Department of Artificial Intelligence, School of Computer Science, UNED, 28040 Madrid, Spain.
| | - Rafael Martínez-Tomás
- Department of Artificial Intelligence, School of Computer Science, UNED, 28040 Madrid, Spain; Joint Research Institute UNED and Health Institute Carlos III (IMIENS), 28040 Madrid, Spain
| | - Pilar Pozo
- Department of Methodology of Behavioral Sciences, Faculty of Psychology, UNED, 28040 Madrid, Spain; Joint Research Institute UNED and Health Institute Carlos III (IMIENS), 28040 Madrid, Spain
| | - Félix de la Paz
- Department of Artificial Intelligence, School of Computer Science, UNED, 28040 Madrid, Spain; Joint Research Institute UNED and Health Institute Carlos III (IMIENS), 28040 Madrid, Spain
| | - Encarnación Sarriá
- Department of Methodology of Behavioral Sciences, Faculty of Psychology, UNED, 28040 Madrid, Spain; Joint Research Institute UNED and Health Institute Carlos III (IMIENS), 28040 Madrid, Spain
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31
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Affiliation(s)
- Evgeni Magid
- Intelligent Robotics Department, Institute of Information Technologies and Intelligent Systems, Kazan Federal University, Kazan, Russian Federation
| | - Aufar Zakiev
- Intelligent Robotics Department, Institute of Information Technologies and Intelligent Systems, Kazan Federal University, Kazan, Russian Federation
| | - Tatyana Tsoy
- Intelligent Robotics Department, Institute of Information Technologies and Intelligent Systems, Kazan Federal University, Kazan, Russian Federation
| | - Roman Lavrenov
- Intelligent Robotics Department, Institute of Information Technologies and Intelligent Systems, Kazan Federal University, Kazan, Russian Federation
| | - Albert Rizvanov
- Clinical Research Center for Precision and Regenerative Medicine, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russian Federation
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A Case Study of a Robot-Assisted Speech Therapy for Children with Language Disorders. SUSTAINABILITY 2021. [DOI: 10.3390/su13052771] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The aim of this study was to explore the potential of using a social robot in speech therapy interventions in children. A descriptive and explorative case study design was implemented involving the intervention for language disorder in five children with different needs with an age ranging from 9 to 12 years. Children participated in sessions with a NAO-type robot in individual sessions. Qualitative methods were used to collect data on aspects of viability, usefulness, barriers and facilitators for the child as well as for the therapist in order to obtain an indication of the effects on learning and the achievement of goals. The main results pointed out the affordances and possibilities of the use of a NAO robot in achieving speech therapy and educational goals. A NAO can contribute towards eliciting motivation, readiness towards learning and improving attention span of the children. The results of the study showed the potential that NAO has in therapy and education for children with different disabilities. More research is needed to gain insight into how a NAO can be applied best in speech therapy to make a more inclusive education conclusions.
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Egido-García V, Estévez D, Corrales-Paredes A, Terrón-López MJ, Velasco-Quintana PJ. Integration of a Social Robot in a Pedagogical and Logopedic Intervention with Children: A Case Study. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6483. [PMID: 33202827 PMCID: PMC7697257 DOI: 10.3390/s20226483] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 10/29/2020] [Accepted: 11/11/2020] [Indexed: 11/16/2022]
Abstract
The effectiveness of social robots such as NAO in pedagogical therapies presents a challenge. There is abundant literature focused on therapies using robots with children with autism, but there is a gap to be filled in other educational different needs. This paper describes an experience of using a NAO as an assistant in a logopedic and pedagogical therapy with children with different needs. Even if the initial robot architecture is based on genericbehaviors, the loading and execution time for each specific requirement and the needs of each child in therapy, made it necessary to develop "Adaptive Behaviors". These evolve into an adaptive architecture, appliedto the engineer-therapist-child interaction, requiring the engineer-programmer to be always present during the sessions. Benefits from the point of view of the therapist and the children and the acceptance of NAO in therapy are shown. A robot in speech-therapy sessions can play a positive role in several logopedic aspectsserving as a motivating factor for the children.Future works should be oriented in developing intelligent algorithms so as to eliminate the presence of the engineer-programmer in the sessions. Additional work proposals should consider deepening the psychological aspects of using humanoid robots in educational therapy.
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Affiliation(s)
- Verónica Egido-García
- Vicedean Architecture, Engineering and Design Degree Programs, School of Architecture, Engineering and Design, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain;
| | - David Estévez
- Aerospace and Industrial Engineering Department, School of Architecture, Engineering and Design, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain;
| | - Ana Corrales-Paredes
- Science, Computation and Technology Department, School of Architecture, Engineering and Design, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain;
| | - María-José Terrón-López
- Aerospace and Industrial Engineering Department, School of Architecture, Engineering and Design, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain;
| | - Paloma-Julia Velasco-Quintana
- Academic Model and Digital Transformation, School of Architecture, Engineering and Design, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain
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Moffett JW, Folse JAG, Palmatier RW. A theory of multiformat communication: mechanisms, dynamics, and strategies. JOURNAL OF THE ACADEMY OF MARKETING SCIENCE 2020; 49:441-461. [PMID: 33199929 PMCID: PMC7658432 DOI: 10.1007/s11747-020-00750-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 09/30/2020] [Indexed: 06/11/2023]
Abstract
Extant communication theories predate the explosion of digital formats and technological advances such as virtual reality, which likely explains their predominant focus on traditional and format-level (e.g., face-to-face, email) rather than digital or characteristic-level (e.g., visual cues, synchronicity) design decisions. Firms thus lack insights into how to create and use emerging digital formats, individually or synergistically. To establish a holistic framework of bilateral multiformat communication for relationship marketing, this article reviews communication theory to establish a foundation for understanding multiformat communication and to identify any gaps (e.g., AI agents, simulated cues). The authors then review bilateral communication research in light of the identified theoretical gaps, to inform their framework. Finally, by decomposing these formats according to six fundamental characteristics, they predict how each characteristic might promote effective, efficient, and experiential communication goals, in light of distinct message, temporal, and dyadic factors. Ultimately, these combined insights reveal an overarching framework, with characteristic-level propositions grouped into five key themes, that can serve as a platform for academics and managers to develop multiformat communication theory and relationship strategies. SUPPLEMENTARY INFORMATION The online version of this article (10.1007/s11747-020-00750-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jordan W. Moffett
- Department of Marketing, University of Kentucky, Gatton College of Business and Economics, 550 South Limestone, Lexington, KY 40506 USA
| | - Judith Anne Garretson Folse
- Department of Marketing, Ourso Family Distinguished Chair in Marketing Research, Louisiana State University, E.J. Ourso College of Business, 2111 Business Education Complex, Baton Rouge, LA 70803 USA
| | - Robert W. Palmatier
- Department of Marketing, John C. Narver Chair of Business Administration, University of Washington, Foster Business School, Box #: 353226, Seattle, Washington, DC 98195 USA
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35
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An Affective and Cognitive Toy to Support Mood Disorders. INFORMATICS 2020. [DOI: 10.3390/informatics7040048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Affective computing is a branch of artificial intelligence that aims at processing and interpreting emotions. In this study, we implemented sensors/actuators into a stuffed toy mammoth, which allows the toy to have an affective and cognitive basis to its communication. The goal is for therapists to use this as a tool during their therapy sessions that work with patients with mood disorders. The toy detects emotion and provides a dialogue that would guide a session aimed at working with emotional regulation and perception. These technical capabilities are possible by employing IBM Watson’s services, implemented into a Raspberry Pi Zero. In this paper, we delve into its evaluation with neurotypical adolescents, a panel of experts, and other professionals. The evaluation aims were to perform a technical and application validation for use in therapy sessions. The results of the evaluations are generally positive, with an 87% accuracy for emotion recognition, and an average usability score of 77.5 for experts (n = 5), and 64.35 for professionals (n = 23). We add to that information some of the issues encountered, its effects on applicability, and future work to be done.
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The Effects of Long-Term Child–Robot Interaction on the Attention and the Engagement of Children with Autism. ROBOTICS 2020. [DOI: 10.3390/robotics9040079] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Using a social robot has been proven to have multiple benefits for the training of children with Autism Spectrum Disorder (ASD). However, there is no clarity on the impact of the interaction quality between a child with ASD and a robot on the effectiveness of the therapy. Previous research showed that the use of a robot in Pivotal Response Treatment (PRT) could be an effective treatment component in diminishing ASD-related symptoms. Further analyzing the data from a randomized controlled trial of PRT treatment, we looked at the long-term effects of child–robot game interactions to see whether the interaction quality changes over time. The attention and the engagement of six children were measured through the observation of non-verbal behavior at three different stages in the treatment that took 20 sessions per child. The gaze and arm/hand behavior of the participants towards the robot, the game, and other present humans were observed. The analysis showed no significant decrease in the attention and the engagement of the children towards the robot and the game. However, the attention and engagement toward the parents of the children increased. We conclude that the main result of sustained attention and engagement with the robot is due to the personalization of the games to meet the specific needs of this user group. These specific needs are met through inclusion of variability to the level of development and personal choice of each participating child. We see the additional finding of increased attention towards the parents as especially positive since the children are expected to improve in human–human interaction as a result of this treatment.
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37
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An Open-Source Social Robot Based on Compliant Soft Robotics for Therapy with Children with ASD. ACTUATORS 2020. [DOI: 10.3390/act9030091] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
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.
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38
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Saleh MA, Hanapiah FA, Hashim H. Robot applications for autism: a comprehensive review. Disabil Rehabil Assist Technol 2020; 16:580-602. [PMID: 32706602 DOI: 10.1080/17483107.2019.1685016] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
PURPOSE Technological advances in robotics have brought about exciting developments in different areas such as education, training, and therapy. Recent research has suggested that the robot can be even more effective in rehabilitation, therapy, and education for individuals with Autism Spectrum Disorder (ASD). In this paper, a comprehensive review of robotic technology for children with ASD is presented wherein a large number of journals and conference proceedings in science and engineering search engines' databases were implicated. MATERIALS AND METHODS A search for related literature was conducted in three search engines' databases, Web of Science, Scopus, and IEEE Xplore. Thematic keywords were used to identify articles in the recent ten years in titles, keywords, and abstracts. The retrieved articles were filtered, analysed, and evaluated based on specific inclusion and exclusion criteria. RESULTS A total of 208 studies were retrieved, while 166 met the inclusion criteria. The selected studies were reviewed according to the type of robot, the participants, objectives, and methods. 68 robots were used in all studies, NAO robot was used in 30.5% of those studies. The total number of participants in all studies was 1671. The highest percentage of the studies reviewed were dedicated to augmenting the learning skills. CONCLUSIONS Robots and the associated schemes were used to determine their feasibility and validity for augmenting the learning skills of autistic children. Most of the studies reviewed were focused on improving the social communication skills of autistic children and measuring the extent of robot mitigation of stereotyped autistic behaviours.Implications for rehabilitationSocial robots are not considered as promising tools to be utilized for rehabilitation of autistic children only, but also has been used for children and young people with severe intellectual disability.Rehabilitation for individuals with ASD using robots can augment their cognitive and social skills, but further studies should be conducted to clarify its effectiveness based on other factors such as sex, age and IQ of the participates.Robotic-based rehabilitation is not limited to the physical robots only, but virtual robots have been used also, whereas each of which can be used individually or simultaneously. However, further study is required to assess the extent of its efficiency and effectiveness for both cases.
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Affiliation(s)
| | | | - Habibah Hashim
- Faculty ofElectrical Engineering, UiTM, Shah Alam, Malaysia
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39
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Abstract
As the field of social robotics has been dynamically growing and expanding over various areas of research and application, in which robots can be of assistance and companionship for humans, this paper offers a different perspective on a role that social robots can also play, namely the role of informing us about flexibility of human mechanisms of social cognition. The paper focuses on studies in which robots have been used as a new type of "stimuli" in psychological experiments to examine whether similar mechanisms of social cognition would be activated in interaction with a robot, as would be elicited in interaction with another human. Analysing studies in which a direct comparison has been made between a robot and a human agent, the paper examines whether for robot agents, the brain re-uses the same mechanisms that have been developed for interaction with other humans in terms of perception, action representation, attention and higher-order social cognition. Based on this analysis, the paper concludes that the human socio-cognitive mechanisms, in adult brains, are sufficiently flexible to be re-used for robotic agents, at least for those that have some level of resemblance to humans.
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40
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Robaczewski A, Bouchard J, Bouchard K, Gaboury S. Socially Assistive Robots: The Specific Case of the NAO. Int J Soc Robot 2020. [DOI: 10.1007/s12369-020-00664-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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41
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Social engagement of children with autism spectrum disorder (ASD) in imitating a humanoid robot: a case study. SN APPLIED SCIENCES 2020. [DOI: 10.1007/s42452-020-2802-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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42
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van den Berk-Smeekens I, van Dongen-Boomsma M, De Korte MWP, Den Boer JC, Oosterling IJ, Peters-Scheffer NC, Buitelaar JK, Barakova EI, Lourens T, Staal WG, Glennon JC. Adherence and acceptability of a robot-assisted Pivotal Response Treatment protocol for children with autism spectrum disorder. Sci Rep 2020; 10:8110. [PMID: 32415231 PMCID: PMC7229010 DOI: 10.1038/s41598-020-65048-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 04/20/2020] [Indexed: 12/16/2022] Open
Abstract
The aim of this study is to present a robot-assisted therapy protocol for children with ASD based on the current state-of-the-art in both ASD intervention research and robotics research, and critically evaluate its adherence and acceptability based on child as well as parent ratings. The robot-assisted therapy was designed based on motivational components of Pivotal Response Treatment (PRT), a highly promising and feasible intervention focused at training “pivotal” (key) areas such as motivation for social interaction and self-initiations, with the goal of establishing collateral gains in untargeted areas of functioning and development, affected by autism spectrum disorders. Overall, children (3–8 y) could adhere to the robot-assisted therapy protocol (Mean percentage of treatment adherence 85.5%), showed positive affect ratings after therapy sessions (positive in 86.6% of sessions) and high robot likability scores (high in 79.4% of sessions). Positive likability ratings were mainly given by school-aged children (H(1) = 7.91, p = .005) and related to the movements, speech and game scenarios of the robot. Parent ratings on the added value of the robot were mainly positive (Mean of 84.8 on 0–100 scale), while lower parent ratings were related to inflexibility of robot behaviour.
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Affiliation(s)
- Iris van den Berk-Smeekens
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands. .,Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands.
| | - Martine van Dongen-Boomsma
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands
| | - Manon W P De Korte
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands
| | - Jenny C Den Boer
- Karakter Child and Adolescent Psychiatry, Postbus 68, 6710 BB, Ede, The Netherlands
| | - Iris J Oosterling
- Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands
| | - Nienke C Peters-Scheffer
- Behavioural Science Institute, Radboud University Nijmegen, PO Box 9104, 6500 HE, Nijmegen, The Netherlands.,Driestroom, PO box 139, 6660 AC, Elst, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands
| | - Emilia I Barakova
- Faculty of Industrial Design, University of Technology, Eindhoven, P.O. Box 513 5600 MB, Eindhoven, The Netherlands
| | - Tino Lourens
- TiViPE, Kanaaldijk ZW 11, 5706 LD, Helmond, The Netherlands
| | - Wouter G Staal
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Reinier Postlaan 12, 6525 GC, Nijmegen, The Netherlands.,Institute for Brian and Cognition, Leiden University, P.O. Box 9600 (C2-S), 2300 RC, Leiden, Netherlands
| | - Jeffrey C Glennon
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, P.O. Box 9104, 6500 HB, Nijmegen, The Netherlands
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Javed H, Lee W, Park CH. Toward an Automated Measure of Social Engagement for Children With Autism Spectrum Disorder-A Personalized Computational Modeling Approach. Front Robot AI 2020; 7:43. [PMID: 33501211 PMCID: PMC7805713 DOI: 10.3389/frobt.2020.00043] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 03/12/2020] [Indexed: 11/15/2022] Open
Abstract
Social engagement is a key indicator of an individual's socio-emotional and cognitive states. For a child with Autism Spectrum Disorder (ASD), this serves as an important factor in assessing the quality of the interactions and interventions. So far, qualitative measures of social engagement have been used extensively in research and in practice, but a reliable, objective, and quantitative measure is yet to be widely accepted and utilized. In this paper, we present our work on the development of a framework for the automated measurement of social engagement in children with ASD that can be utilized in real-world settings for the long-term clinical monitoring of a child's social behaviors as well as for the evaluation of the intervention methods being used. We present a computational modeling approach to derive the social engagement metric based on a user study with children between the ages of 4 and 12 years. The study was conducted within a child-robot interaction setting that targets sensory processing skills in children. We collected video, audio and motion-tracking data from the subjects and used them to generate personalized models of social engagement by training a multi-channel and multi-layer convolutional neural network. We then evaluated the performance of this network by comparing it with traditional classifiers and assessed its limitations, followed by discussions on the next steps toward finding a comprehensive and accurate metric for social engagement in ASD.
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Affiliation(s)
- Hifza Javed
- Assistive Robotics and Telemedicine Laboratory, Department of Biomedical Engineering, School of Engineering and Applied Science, The George Washington University, Washington, DC, United States
| | - WonHyong Lee
- School of Computer Science and Electrical Engineering, Handong Global University, Pohang, South Korea
| | - Chung Hyuk Park
- Assistive Robotics and Telemedicine Laboratory, Department of Biomedical Engineering, School of Engineering and Applied Science, The George Washington University, Washington, DC, United States
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44
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Schadenberg BR, Reidsma D, Heylen DKJ, Evers V. Differences in Spontaneous Interactions of Autistic Children in an Interaction With an Adult and Humanoid Robot. Front Robot AI 2020; 7:28. [PMID: 33501197 PMCID: PMC7805683 DOI: 10.3389/frobt.2020.00028] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 02/19/2020] [Indexed: 11/13/2022] Open
Abstract
Robots are promising tools for promoting engagement of autistic children in interventions and thereby increasing the amount of learning opportunities. However, designing deliberate robot behavior aimed at engaging autistic children remains challenging. Our current understanding of what interactions with a robot, or facilitated by a robot, are particularly motivating to autistic children is limited to qualitative reports with small sample sizes. Translating insights from these reports to design is difficult due to the large individual differences among autistic children in their needs, interests, and abilities. To address these issues, we conducted a descriptive study and report on an analysis of how 31 autistic children spontaneously interacted with a humanoid robot and an adult within the context of a robot-assisted intervention, as well as which individual characteristics were associated with the observed interactions. For this analysis, we used video recordings of autistic children engaged in a robot-assisted intervention that were recorded as part of the DE-ENIGMA database. The results showed that the autistic children frequently engaged in exploratory and functional interactions with the robot spontaneously, as well as in interactions with the adult that were elicited by the robot. In particular, we observed autistic children frequently initiating interactions aimed at making the robot do a certain action. Autistic children with stronger language ability, social functioning, and fewer autism spectrum-related symptoms, initiated more functional interactions with the robot and more robot-elicited interactions with the adult. We conclude that the children's individual characteristics, in particular the child's language ability, can be indicative of which types of interaction they are more likely to find interesting. Taking these into account for the design of deliberate robot behavior, coupled with providing more autonomy over the robot's behavior to the autistic children, appears promising for promoting engagement and facilitating more learning opportunities.
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Affiliation(s)
- Bob R Schadenberg
- Human Media Interaction, University of Twente, Enschede, Netherlands
| | - Dennis Reidsma
- Human Media Interaction, University of Twente, Enschede, Netherlands
| | - Dirk K J Heylen
- Human Media Interaction, University of Twente, Enschede, Netherlands
| | - Vanessa Evers
- Human Media Interaction, University of Twente, Enschede, Netherlands.,Institute of Science and Technology for Humanity, Nanyang Technological University, Singapore, Singapore
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45
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Abstract
Over one billion people in the world suffer from some form of disability. Nevertheless, according to the World Health Organization, people with disabilities are particularly vulnerable to deficiencies in services, such as health care, rehabilitation, support, and assistance. In this sense, recent technological developments can mitigate these deficiencies, offering less-expensive assistive systems to meet users’ needs. This paper reviews and summarizes the research efforts toward the development of these kinds of systems, focusing on two social groups: older adults and children with autism.
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46
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Ismail LI, Hanapiah FA, Belpaeme T, Dambre J, Wyffels F. Analysis of Attention in Child–Robot Interaction Among Children Diagnosed with Cognitive Impairment. Int J Soc Robot 2020. [DOI: 10.1007/s12369-020-00628-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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Syriopoulou-Delli CK, Gkiolnta E. Review of assistive technology in the training of children with autism spectrum disorders. INTERNATIONAL JOURNAL OF DEVELOPMENTAL DISABILITIES 2020; 68:73-85. [PMID: 35309695 PMCID: PMC8928843 DOI: 10.1080/20473869.2019.1706333] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 12/10/2019] [Accepted: 12/11/2019] [Indexed: 05/30/2023]
Abstract
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.
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Affiliation(s)
| | - Eleni Gkiolnta
- Department of Educational and Social Policy, University of Macedonia, Thessaloniki, Greece
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48
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Kossewska J, Kłosowska J. Acceptance of Robot‐Mediated Teaching and Therapy for Children With Atypical Development by Polish Professionals. JOURNAL OF POLICY AND PRACTICE IN INTELLECTUAL DISABILITIES 2020. [DOI: 10.1111/jppi.12296] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Abstract
This paper discusses the nuances of a social robot, how and why social robots are becoming increasingly significant, and what they are currently being used for. This paper also reflects on the current design of social robots as a means of interaction with humans and also reports potential solutions about several important questions around the futuristic design of these robots. The specific questions explored in this paper are: “Do social robots need to look like living creatures that already exist in the world for humans to interact well with them?”; “Do social robots need to have animated faces for humans to interact well with them?”; “Do social robots need to have the ability to speak a coherent human language for humans to interact well with them?” and “Do social robots need to have the capability to make physical gestures for humans to interact well with them?”. This paper reviews both verbal as well as nonverbal social and conversational cues that could be incorporated into the design of social robots, and also briefly discusses the emotional bonds that may be built between humans and robots. Facets surrounding acceptance of social robots by humans and also ethical/moral concerns have also been discussed.
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Javed H, Burns R, Jeon M, Howard AM, Park CH. A Robotic Framework to Facilitate Sensory Experiences for Children with Autism Spectrum Disorder: A Preliminary Study. ACM TRANSACTIONS ON HUMAN-ROBOT INTERACTION 2019; 9:3. [PMID: 33829148 PMCID: PMC8023221 DOI: 10.1145/3359613] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 08/01/2019] [Indexed: 02/03/2023]
Abstract
The diagnosis of Autism Spectrum Disorder (ASD) in children is commonly accompanied by a diagnosis of sensory processing disorders. Abnormalities are usually reported in multiple sensory processing domains, showing a higher prevalence of unusual responses, particularly to tactile, auditory and visual stimuli. This paper discusses a novel robot-based framework designed to target sensory difficulties faced by children with ASD in a controlled setting. The setup consists of a number of sensory stations, together with two different robotic agents that navigate the stations and interact with the stimuli. These stimuli are designed to resemble real world scenarios that form a common part of one's everyday experiences. Given the strong interest of children with ASD in technology in general and robots in particular, we attempt to utilize our robotic platform to demonstrate socially acceptable responses to the stimuli in an interactive, pedagogical setting that encourages the child's social, motor and vocal skills, while providing a diverse sensory experience. A preliminary user study was conducted to evaluate the efficacy of the proposed framework, with a total of 18 participants (5 with ASD and 13 typically developing) between the ages of 4 and 12 years. We derive a measure of social engagement, based on which we evaluate the effectiveness of the robots and sensory stations in order to identify key design features that can improve social engagement in children.
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