Advertisement

Toward Robot-Assisted Psychosocial Intervention for Children with Autism Spectrum Disorder (ASD)

  • Vasiliki Holeva
  • Vasiliki-Aliki Nikopoulou
  • Maria Papadopoulou
  • Eleni Vrochidou
  • George A. Papakostas
  • Vassilis G. KaburlasosEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11876)

Abstract

The effectiveness of social robots in education is typically demonstrated, circumstantially, involving small samples of students [1]. Our interest here is in special education in Greece regarding Autism Spectrum Disorder (ASD) involving large samples of children students. Following a recent work review, this paper reports the specifications of a protocol for testing the effectiveness of robot (NAO)-based treatment of ASD children compared to conventional human (therapist)-based treatment. The proposed protocol has been developed by the collaboration of a clinical scientific team with a technical scientific team. The modular structure of the aforementioned protocol allows for implementing parametrically a number of tools and/or theories such as the theory-of-mind account from psychology; moreover, the engagement of the innovative Lattice Computing (LC) information processing paradigm is considered here toward making the robot more autonomous. This paper focuses on the methodological and design details of the proposed intervention protocol that is underway; the corresponding results will be reported in a future publication.

Keywords

Social robots Autism spectrum disorders Human-robot interaction Psychological intervention Protocol design Robot-assisted therapy 

Notes

Acknowledgment

This research has been co-financed by the European Union and Greek natal ionfunds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-00929).

References

  1. 1.
    Pedersen, B.K.M.K., Larsen, J.C., Nielsen, J.: The effect of commercially available educational robotics: a systematic review. In: Merdan, M., Lepuschitz, W., Koppensteiner, G., Balogh, R., Obdržálek, D. (eds.) RiE 2019. AISC, vol. 1023, pp. 14–27. Springer, Cham (2020).  https://doi.org/10.1007/978-3-030-26945-6_2CrossRefGoogle Scholar
  2. 2.
    Battle, D.E.: Diagnostic and statistical manual of mental disorders (DSM). CoDAS 25, 191–192 (2013)CrossRefGoogle Scholar
  3. 3.
    Cabibihan, J.J., Javed, H., Ang, M., Aljunied, S.M.: Why Robots? A survey on the roles and benefits of social robots in the therapy of children with autism. Int. J. Soc. Robot. (2013).  https://doi.org/10.1007/s12369-013-0202-2CrossRefGoogle Scholar
  4. 4.
    Huijnen, C.A.G.J., Lexis, M.A.S., Jansens, R., de Witte, L.P.: Mapping robots to therapy and educational objectives for children with autism spectrum disorder. J. Autism Dev. Disord. (2016).  https://doi.org/10.1007/s10803-016-2740-6CrossRefGoogle Scholar
  5. 5.
    Kaburlasos, V.G., Vrochidou, E.: Social robots for pedagogical rehabilitation: trends and novel modeling principles. In: Global, I. (ed.) Cyber-Physical Systems for Social Applications, pp. 1–12 (2019)Google Scholar
  6. 6.
    Richardson, K., et al.: Robot enhanced therapy for children with autism (DREAM): a social model of autism. IEEE Technol. Soc. Mag. 37, 30–39 (2018).  https://doi.org/10.1109/MTS.2018.2795096CrossRefGoogle Scholar
  7. 7.
    Diehl, J.J., Schmitt, L.M., Villano, M., Crowell, C.R.: The clinical use of robots for individuals with autism spectrum disorders: a critical review (2012).  https://doi.org/10.1016/j.rasd.2011.05.006CrossRefGoogle Scholar
  8. 8.
    Pennisi, P., et al.: Autism and social robotics: a systematic review (2016).  https://doi.org/10.1002/aur.1527CrossRefGoogle Scholar
  9. 9.
    Robinson, N.L., Cottier, T.V., Kavanagh, D.J.: Psychosocial health interventions by social robots: systematic review of randomized controlled trials. J. Med. Internet Res. 21, e13203 (2019)CrossRefGoogle Scholar
  10. 10.
    Attwood, T., Scarpa, A.: Modifications of cognitive-behavioral therapy for children and adolescents with high-functioning ASD and their common difficulties. In: Scarpa, A., Williams White, S., Attwood, T. (eds.) CBT for Children and Adolescents with High-Functioning Autism Spectrum Disorders, pp. 27–44, 329 p. Guilford Press, New York (2013)Google Scholar
  11. 11.
    Social Robots as Tools in Special Education. http://www.koiro3e.eu/
  12. 12.
    Kaburlasos, V.G., Dardani, C., Dimitrova, M., Amanatiadis, A.: Multi-robot engagement in special education: a preliminary study in autism. In: 2018 IEEE International Conference on Consumer Electronics, ICCE 2018 (2018).  https://doi.org/10.1109/ICCE.2018.8326267
  13. 13.
    Bharatharaj, J., Huang, L., Al-Jumaily, A., Mohan, R.E., Krägeloh, C.: Sociopsychological and physiological effects of a robot-assisted therapy for children with autism. Int. J. Adv. Robot. Syst. (2017).  https://doi.org/10.1177/1729881417736895CrossRefGoogle Scholar
  14. 14.
    Lytridis, C., et al.: Audio signal recognition based on internals’ numbers (INs) classification techniques. In: 10th International Conference on Information, Intelligence, Systems and Applications (IISA 2019) (2019)Google Scholar
  15. 15.
    Baron-Cohen, S.: Theory of mind and autism: a review. Int. Rev. Res. Ment. Retard. 23, 169–184 (2000)CrossRefGoogle Scholar
  16. 16.
    Lovaas, O.I.: Behavioral treatment and normal educational and intellectual functioning in young autistic children. J. Consult. Clin. Psychol. (1987)Google Scholar
  17. 17.
    Wechsler, D.: Wechsler Preschool and Primay Scale of Intelligence - Third Edition (WPPSI-III) Technical and Interpretive Manual. Psychological Corporation, San Antonio (2002)Google Scholar
  18. 18.
    Weiss, L.G., Locke, V., Pan, T., Harris, J.G., Saklofske, D.H., Prifitera, A.: Wechsler intelligence scale for children—fifth edition. In: WISC-V (2019).  https://doi.org/10.1016/b978-0-12-815744-2.00005-7CrossRefGoogle Scholar
  19. 19.
    Schopler, E., Van Bourgondien, M.E., Wellman, G.J., Love, S.R.: The Childhood Autism Rating Scale, 2nd edn. West Psychological Services, Los Angeles (2010)Google Scholar
  20. 20.
    Le Couteur, A., Lord, C., Rutter, M.: The autism diagnostic interview- revised (2003)Google Scholar
  21. 21.
    Korkman, M., Kirk, U., Kemp, S.: Design and purpose of the NEPSY-II. In: The NEPSY (2007)Google Scholar
  22. 22.
    Achenbach, T.: Manual for the ASEBA School-Age Forms & Profiles An Integrated System of Multi-informant Assessment. Research Center for Children (2007)Google Scholar
  23. 23.
    Goodman, R.: The strengths and difficulties questionnaire: a research note. J. Child Psychol. Psychiatry Allied Discip. (1997).  https://doi.org/10.1111/j.1469-7610.1997.tb01545.xCrossRefGoogle Scholar
  24. 24.
    Robins, B., Otero, N., Ferrari, E., Dautenhahn, K.: Eliciting requirements for a robotic toy for children with autism - results from user panels. In: Proceedings - IEEE International Workshop on Robot and Human Interactive Communication (2007).  https://doi.org/10.1109/ROMAN.2007.4415061

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Vasiliki Holeva
    • 1
  • Vasiliki-Aliki Nikopoulou
    • 1
  • Maria Papadopoulou
    • 2
  • Eleni Vrochidou
    • 3
  • George A. Papakostas
    • 3
  • Vassilis G. Kaburlasos
    • 3
    Email author
  1. 1.1st Psychiatric ClinicPapageorgiou General Hospital, Aristotle University of ThessalonikiThessalonikiGreece
  2. 2.Division of Child Neurology and Metabolic Disorders, 4th Department of PediatricsPapageorgiou General Hospital, Aristotle University of ThessalonikiThessalonikiGreece
  3. 3.HUman-MAchines INteraction Laboratory (HUMAIN-Lab)International Hellenic UniversityKavalaGreece

Personalised recommendations