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Wedasingha N, Samarasinghe P, Senevirathna L, Papandrea M, Puiatti A, Rankin D. Automated anomalous child repetitive head movement identification through transformer networks. Phys Eng Sci Med 2023; 46:1427-1445. [PMID: 37814077 DOI: 10.1007/s13246-023-01309-5] [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: 02/01/2023] [Accepted: 07/24/2023] [Indexed: 10/11/2023]
Abstract
The increasing prevalence of behavioral disorders in children is of growing concern within the medical community. Recognising the significance of early identification and intervention for atypical behaviors, there is a consensus on their pivotal role in improving outcomes. Due to inadequate facilities and a shortage of medical professionals with specialized expertise, traditional diagnostic methods have been unable to effectively address the rising incidence of behavioral disorders. Hence, there is a need to develop automated approaches for the diagnosis of behavioral disorders in children, to overcome the challenges with traditional methods. The purpose of this study is to develop an automated model capable of analyzing videos to differentiate between typical and atypical repetitive head movements in. To address problems resulting from the limited availability of child datasets, various learning methods are employed to mitigate these issues. In this work, we present a fusion of transformer networks, and Non-deterministic Finite Automata (NFA) techniques, which classify repetitive head movements of a child as typical or atypical based on an analysis of gender, age, and type of repetitive head movement, along with count, duration, and frequency of each repetitive head movement. Experimentation was carried out with different transfer learning methods to enhance the performance of the model. The experimental results on five datasets: NIR face dataset, Bosphorus 3D face dataset, ASD dataset, SSBD dataset, and the Head Movements in the Wild dataset, indicate that our proposed model has outperformed many state-of-the-art frameworks when distinguishing typical and atypical repetitive head movements in children.
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Affiliation(s)
- Nushara Wedasingha
- Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Rd, Malabe, 10115, Colombo, Sri Lanka.
| | - Pradeepa Samarasinghe
- Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Rd, Malabe, 10115, Colombo, Sri Lanka
| | - Lasantha Senevirathna
- Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Rd, Malabe, 10115, Colombo, Sri Lanka
| | - Michela Papandrea
- Information Systems and Networking Institute (ISIN), University of Applied Sciences and Arts of Southern Switzerland, Via Pobiette, Manno, 6928, Switzerland
| | - Alessandro Puiatti
- Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Via Pobiette, Manno, 6928, Switzerland
| | - Debbie Rankin
- School of Computing, Engineering and Intelligent Systems, Ulster University, Northland Road, Derry-Londonderry, BT48 7JL, Northern Ireland, UK
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Advances in Autism Research: Series II. Brain Sci 2023; 13:brainsci13020332. [PMID: 36831875 PMCID: PMC9954114 DOI: 10.3390/brainsci13020332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
"Advances in Autism Research: Series II" is a continuation of the important Special Issue (SI) published in 2020 that collected 50 articles [...].
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Pinto-Bernal MJ, Sierra M. SD, Munera M, Casas D, Villa-Moreno A, Frizera-Neto A, Stoelen MF, Belpaeme T, Cifuentes CA. Do different robot appearances change emotion recognition in children with ASD? Front Neurorobot 2023; 17:1044491. [PMID: 36937553 PMCID: PMC10017775 DOI: 10.3389/fnbot.2023.1044491] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Introduction Socially Assistive Robotics has emerged as a potential tool for rehabilitating cognitive and developmental disorders in children with autism. Social robots found in the literature are often able to teach critical social skills, such as emotion recognition and physical interaction. Even though there are promising results in clinical studies, there is a lack of guidelines on selecting the appropriate robot and how to design and implement the child-robot interaction. Methods This work aims to evaluate the impacts of a social robot designed with three different appearances according to the results of a participatory design (PD) process with the community. A validation study in the emotion recognition task was carried out with 21 children with autism. Results Spectrum disorder results showed that robot-like appearances reached a higher percentage of children's attention and that participants performed better when recognizing simple emotions, such as happiness and sadness. Discussion This study offers empirical support for continuing research on using SAR to promote social interaction with children with ASD. Further long-term research will help to identify the differences between high and low-functioning children.
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Affiliation(s)
| | - Sergio D. Sierra M.
- Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom
| | - Marcela Munera
- Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom
- Department of Biomedical Engineering, Colombian School of Engineering Julio Garavito, Bogotá, Colombia
| | - Diego Casas
- School of Engineering, Science and Technology, Universidad del Rosario, Bogotá, Colombia
| | | | - Anselmo Frizera-Neto
- Electrical Engineering Department, Federal University of Espirito Santo, Victoria, Brazil
| | - Martin F. Stoelen
- Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Norway
| | | | - Carlos A. Cifuentes
- Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom
- School of Engineering, Science and Technology, Universidad del Rosario, Bogotá, Colombia
- *Correspondence: Carlos A. Cifuentes
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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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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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Automatic Assessment of Motor Impairments in Autism Spectrum Disorders: A Systematic Review. Cognit Comput 2022. [DOI: 10.1007/s12559-021-09940-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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7
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Monteleone V, Lo Presti L, La Cascia M, Gauthier S, Xavier J, Zaoui M, Berthoz A, Cohen D, Chetouani M, Anzalone SM. Semiautomatic Behavioral Change-Point Detection: A Case Study Analyzing Children Interactions With a Social Agent. IEEE Trans Cogn Dev Syst 2021. [DOI: 10.1109/tcds.2020.3023196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Brief Report: The Effectiveness of Hugging a Huggable Device Before Having a Conversation with an Unfamiliar Person for Autism Spectrum Disorders. J Autism Dev Disord 2021; 52:3294-3303. [PMID: 34292488 PMCID: PMC9213352 DOI: 10.1007/s10803-021-05173-8] [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] [Accepted: 06/25/2021] [Indexed: 11/17/2022]
Abstract
Sensory overresponsivity (SOR) emerges before anxiety and positively predicts subsequent increasing levels of anxiety in individuals with autism spectrum disorder (ASD). Sensory seeking behavior occurs as compensation for SOR, and individuals may seek sensory input in one sensory domain to compensate for SOR. Tactile seeking behavior is sufficient to decrease social anxiety in communicating with unfamiliar people. We assessed the effectiveness of hugging a huggable device before a conversation for reducing the psychological stress associated with speaking to an unfamiliar person or robot. Our analysis showed a significant effect, with Hugvie contributing to decreased stress for both interlocutors. Thus, this study demonstrated the efficacy of hugging it before conversation, which emphasizes the importance of tactile seeking for individuals with ASD.
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Rakhymbayeva N, Amirova A, Sandygulova A. A Long-Term Engagement with a Social Robot for Autism Therapy. Front Robot AI 2021; 8:669972. [PMID: 34222353 PMCID: PMC8241906 DOI: 10.3389/frobt.2021.669972] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/31/2021] [Indexed: 11/18/2022] Open
Abstract
Social robots are increasingly being used as a mediator between a therapist and a child in autism therapy studies. In this context, most behavioural interventions are typically short-term in nature. This paper describes a long-term study that was conducted with 11 children diagnosed with either Autism Spectrum Disorder (ASD) or ASD in co-occurrence with Attention Deficit Hyperactivity Disorder (ADHD). It uses a quantitative analysis based on behavioural measures, including engagement, valence, and eye gaze duration. Each child interacted with a robot on several occasions in which each therapy session was customized to a child's reaction to robot behaviours. This paper presents a set of robot behaviours that were implemented with the goal to offer a variety of activities to be suitable for diverse forms of autism. Therefore, each child experienced an individualized robot-assisted therapy that was tailored according to the therapist's knowledge and judgement. The statistical analyses showed that the proposed therapy managed to sustain children's engagement. In addition, sessions containing familiar activities kept children more engaged compared to those sessions containing unfamiliar activities. The results of the interviews with parents and therapists are discussed in terms of therapy recommendations. The paper concludes with some reflections on the current study as well as suggestions for future studies.
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Affiliation(s)
- Nazerke Rakhymbayeva
- Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Aida Amirova
- Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Anara Sandygulova
- Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan
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Nie G, Ullal A, Zheng Z, Swanson AR, Weitlauf AS, Warren ZE, Sarkar N. An Immersive Computer-Mediated Caregiver-Child Interaction System for Young Children With Autism Spectrum Disorder. IEEE Trans Neural Syst Rehabil Eng 2021; 29:884-893. [PMID: 33945481 PMCID: PMC8189254 DOI: 10.1109/tnsre.2021.3077480] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Autism Spectrum Disorder (ASD) affects 1 in 54 children in the United States. A core social communication skill negatively impacted by ASD is joint attention (JA), which influences the development of language, cognitive, and social skills from infancy onward. Although several technology-based JA studies have shown potential, they primarily focus on response to joint attention (RJA). The other important component of JA, the initiation of joint attention (IJA), has received less attention from a technology-based intervention perspective. In this work, we present an immersive Computer-mediated Caregiver-Child Interaction (C3I) system to help children with ASD practice IJA skills. C3I is a novel computerized intervention system that integrates a caregiver in the teaching loop, thereby preserving the advantages of both human and computer-administered intervention. A feasibility study with 6 dyads (caregiver-child with ASD) was conducted. A near significant increase with medium effect size on IJA performance was observed. Meanwhile, physiology-based stress analysis showed that C3I did not increase stress of the caregivers over the course of the study. To the best of our knowledge, this is the first autonomous system designed for teaching IJA skills to children with ASD incorporating caregivers within the loop to enhance the potential for generalization in real-world.
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Dai L, Liu J, Ju Z, Gao Y. Attention Mechanism based Real Time Gaze Tracking in Natural Scenes with Residual Blocks. IEEE Trans Cogn Dev Syst 2021. [DOI: 10.1109/tcds.2021.3064280] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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12
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Abubshait A, Wykowska A. Repetitive Robot Behavior Impacts Perception of Intentionality and Gaze-Related Attentional Orienting. Front Robot AI 2020; 7:565825. [PMID: 33501328 PMCID: PMC7805881 DOI: 10.3389/frobt.2020.565825] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/25/2020] [Indexed: 11/22/2022] Open
Abstract
Gaze behavior is an important social signal between humans as it communicates locations of interest. People typically orient their attention to where others look as this informs about others' intentions and future actions. Studies have shown that humans can engage in similar gaze behavior with robots but presumably more so when they adopt the intentional stance toward them (i.e., believing robot behaviors are intentional). In laboratory settings, the phenomenon of attending toward the direction of others' gaze has been examined with the use of the gaze-cueing paradigm. While the gaze-cueing paradigm has been successful in investigating the relationship between adopting the intentional stance toward robots and attention orienting to gaze cues, it is unclear if the repetitiveness of the gaze-cueing paradigm influences adopting the intentional stance. Here, we examined if the duration of exposure to repetitive robot gaze behavior in a gaze-cueing task has a negative impact on subjective attribution of intentionality. Participants performed a short, medium, or long face-to-face gaze-cueing paradigm with an embodied robot while subjective ratings were collected pre and post the interaction. Results show that participants in the long exposure condition had the smallest change in their intention attribution scores, if any, while those in the short exposure condition had a positive change in their intention attribution, indicating that participants attributed more intention to the robot after short interactions. The results also show that attention orienting to robot gaze-cues was positively related to how much intention was attributed to the robot, but this relationship became more negative as the length of exposure increased. In contrast to subjective ratings, the gaze-cueing effects (GCEs) increased as a function of the duration of exposure to repetitive behavior. The data suggest a tradeoff between the desired number of trials needed for observing various mechanisms of social cognition, such as GCEs, and the likelihood of adopting the intentional stance toward a robot.
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Affiliation(s)
- Abdulaziz Abubshait
- Social Cognition in Human-Robot Interaction (S4HRI) Unit, Istituto Italiano di Tecnologia, Genova, Italy
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Huang L, Wei W, Liu Z, Zhang T, Wang J, Xu L, Chen W, Le Meur O. Effective schizophrenia recognition using discriminative eye movement features and model-metric based features. Pattern Recognit Lett 2020. [DOI: 10.1016/j.patrec.2020.09.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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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: 11] [Impact Index Per Article: 2.8] [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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Dai L, Liu J, Ju Z, Gao Y. Iris center localization using energy map synthesis based on gradient and isophote. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020. [DOI: 10.3233/jifs-191281] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Lihong Dai
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jinguo Liu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China
| | - Zhaojie Ju
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China
- School of Computing, University of Portsmouth, Portsmouth, UK
| | - Yang Gao
- Space Technology for Autonomous & Robotic systems Laboratory (STAR LAB), Surrey Space Centre, University of Surrey, Guildford, UK
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Chevalier P, Kompatsiari K, Ciardo F, Wykowska A. Examining joint attention with the use of humanoid robots-A new approach to study fundamental mechanisms of social cognition. Psychon Bull Rev 2020; 27:217-236. [PMID: 31848909 PMCID: PMC7093354 DOI: 10.3758/s13423-019-01689-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
This article reviews methods to investigate joint attention and highlights the benefits of new methodological approaches that make use of the most recent technological developments, such as humanoid robots for studying social cognition. After reviewing classical approaches that address joint attention mechanisms with the use of controlled screen-based stimuli, we describe recent accounts that have proposed the need for more natural and interactive experimental protocols. Although the recent approaches allow for more ecological validity, they often face the challenges of experimental control in more natural social interaction protocols. In this context, we propose that the use of humanoid robots in interactive protocols is a particularly promising avenue for targeting the mechanisms of joint attention. Using humanoid robots to interact with humans in naturalistic experimental setups has the advantage of both excellent experimental control and ecological validity. In clinical applications, it offers new techniques for both diagnosis and therapy, especially for children with autism spectrum disorder. The review concludes with indications for future research, in the domains of healthcare applications and human-robot interaction in general.
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Affiliation(s)
- Pauline Chevalier
- Social Cognition in Human-Robot Interaction Unit, Istituto Italiano di Tecnologia, Genoa, Italy.
| | - Kyveli Kompatsiari
- Social Cognition in Human-Robot Interaction Unit, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Francesca Ciardo
- Social Cognition in Human-Robot Interaction Unit, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Agnieszka Wykowska
- Social Cognition in Human-Robot Interaction Unit, Istituto Italiano di Tecnologia, Genoa, Italy
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A Randomized Controlled Trial of an Intelligent Robotic Response to Joint Attention Intervention System. J Autism Dev Disord 2020; 50:2819-2831. [DOI: 10.1007/s10803-020-04388-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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18
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Lachal J, Piot MA, Sibeoni J. [What university child psychiatry for tomorrow?]. Encephale 2019; 46:162-163. [PMID: 31495552 DOI: 10.1016/j.encep.2019.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 07/09/2019] [Indexed: 10/26/2022]
Affiliation(s)
- J Lachal
- AP-HP, Hôpital Cochin, Maison de Solenn, 75014 Paris, France; Université de Paris, PCPP, 92100 Boulogne-Billancourt, France; CESP, faculté de médecine, université Paris-Sud, faculté de médecine, UVSQ, INSERM, université Paris-Saclay, 94805 Villejuif, France.
| | - M-A Piot
- Université de Paris, PCPP, 92100 Boulogne-Billancourt, France; CESP, faculté de médecine, université Paris-Sud, faculté de médecine, UVSQ, INSERM, université Paris-Saclay, 94805 Villejuif, France; Institut mutualiste Montsouris, 75014 Paris, France
| | - J Sibeoni
- Service universitaire de psychiatrie de l'adolescent, Argenteuil Hospital Centre, 95100 Argenteuil, France; ECSTRRA Team, UMR-1153, Inserm, Paris-Diderot University, Sorbonne Paris-Cité, 75004 Paris, France
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