Identifying Linguistic Cues; Towards Developing Robots With Empathy in Autism Interventions

Vasiliki Aliki Nikopoulou 1, Vasiliki Holeva 1 * , Maria Dialechti Kerasidou 1, Petros Kechayas 1, Maria Papadopoulou 2, Eleni Vrochidou 3, George A. Papakostas 3, Vassilis G. Kaburlasos 3
More Detail
1 Department of Clinical Psychology, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
2 Division of Child Neurology and Metabolic Disorders, 4th Department of Pediatrics, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
3 HUman-MAchines INteraction Laboratory (HUMAINLab), International Hellenic University, Agios Loukas, Kavala, Greece
* Corresponding Author
J CLIN MED KAZ, Volume 2, Issue 56, pp. 27-33. https://doi.org/10.23950/1812-2892-JCMK-00753
OPEN ACCESS 2536 Views 1730 Downloads
Download Full Text (PDF)

ABSTRACT

The last decade autism research has been enhanced by the use of social robots and several studies suggest that children with Autism Spectrum Disorders could benefit from robot-assisted interventions. In order to design and implement therapeutic interventions with robots without interrupting the intervention’s flow, one should take into account possible technical issues that could arise. The main objective of this study was to gather information from experts in the field of autism and develop linguistic cues to which the robot would respond automatically. A qualitative approach was used to explore specialists’ preferences. Online surveys were completed by 33 professionals from different backgrounds to select the vocabulary more often used in psychosocial interventions with autism spectrum disorders children, in specific situations. Six linguistic cues were identified and specific phrases were used so as to accordingly program the robot to show empathy and respond, when a crisis emerges. The session’s flow in robot-enhanced interventions could benefit by controlling robot’s behaviour with linguistic cues phrased by the therapist. The implications of these findings are discussed in relation to pilot implementation. This work consists of a qualitative study aiming at strengthening the application of a larger research intervention protocol to explore the interaction of children with autism spectrum disorder with a social robot.
Keywords: social robots, autism spectrum disorders, human-robot interaction, psychological intervention, robotic empathy, robot-assisted therapy

CITATION

Nikopoulou VA, Holeva V, Kerasidou MD, Kechayas P, Papadopoulou M, Vrochidou E, et al. Identifying Linguistic Cues; Towards Developing Robots With Empathy in Autism Interventions. Journal of Clinical Medicine of Kazakhstan. 2020;2(56):27-33. https://doi.org/10.23950/1812-2892-JCMK-00753

REFERENCES

  • Begum M, Serna RW, Yanco HA. Are robots ready to deliver autism interventions? A comprehensive review. Int J Soc Robot. 2016; 8(2):157-181. https://doi.org/10.1007/s12369-016-0346-y
  • Diehl JJ, Schmitt LM, Villano M, Crowell CR. The clinical use of robots for individuals with autism spectrum disorders: A critical review. Res Autism Spectr Disord. 2012; 6(1):249-262. https://doi.org/10.1016/j.rasd.2011.05.006
  • Cabibihan JJ, Javed H, Ang M, Aljunied SM. Why robots? A survey on the roles and benefits of social robots in the therapy of children with autism. Int J Soc Robot. 2013; 5(4):593-618. https://doi.org/10.1007/s12369-013-0202-2
  • Pennisi P, Tonacci A, Tartarisco G, Billeci L, Ruta L, Gangemi S, Pioggia G. Autism and social robotics: A systematic review. Autism Res. 2016; 9(2):165-183. https://doi.org/10.1002/aur.1527
  • Scassellati B, Admoni H, Matariж M. Robots for use in autism research. Annu Rev Biomed Eng. 2012; 14:275-294. https://doi.org/10.1146/annurev-bioeng-071811-150036
  • Marino F, Chilа P, Sfrazzetto ST, Carrozza C, Crimi I, Failla C, et al. Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders. J Autism Dev Disord. 2019; 1-15. https://doi.org/10.1007/s10803-019-03953-x
  • Watkins L, O'Reilly M, Kuhn M, Gevarter C, Lancioni GE, Sigafoos J, Lang R. A review of peer-mediated social interaction interventions for students with autism in inclusive settings. J Autism Dev Disord. 2015; 45(4):1070-1083. https://doi.org/10.1007/s10803-014-2264-x
  • Yun SS, Choi J, Park SK, Bong GY, Yoo H. Social skills training for children with autism spectrum disorder using a robotic behavioral intervention system. Autism Res. 2017; 10(7):1306-1323. https://doi.org/10.1002/aur.1778
  • Liu X, Wu Q, Zhao W, Luo X. Technology-facilitated diagnosis and treatment of individuals with autism spectrum disorder: An engineering perspective. Appl Sci. 2017; 7(10):1051. https://doi.org/10.3390/app7101051
  • Ehrenreich JT, Fairholme CP, Buzzella BA, Ellard KK, Barlow DH. The role of emotion in psychological therapy. Clin Psychol Sci Pract. 2007; 14(4):422-428. https://doi.org/10.1111/j.1468-2850.2007.00102.x
  • Bohart AC, Elliott R, Greenberg LS, Watson JC. Empathy. In: Norcross JC, editor. Psychotherapy relationships that work: Therapist contributions and responsiveness to patients. New York: Oxford University Press. 2002; 89-108.
  • Esteban PG, Baxter P, Belpaeme T, Billing E, Cai H, Cao HL, et al. How to build a supervised autonomous system for robot-enhanced therapy for children with autism spectrum disorder. PJBRS. 2017; 8(1):18-38. https://doi.org/10.1515/pjbr-2017-0002
  • Huijnen CA, Lexis MA, Jansens R, de Witte LP. How to implement robots in interventions for children with autism? A co-creation study involving people with autism, parents and professionals. J Autism Dev Disord. 2017; 47(10):3079-3096. https://doi.org/10.1007/s10803-017-3235-9
  • Marshall MN. Sampling for qualitative research. J Fam Pract. 1996; 13(6):522-526. https://doi.org/10.1093/fampra/13.6.522
  • Krippendorff K. Content Analysis. An Introduction to Its Methodology. 3rd ed. Thousand Oaks: Sage Publications. 2013.
  • Neuendorf KA. The Content Analysis Guidebook. 2nd ed. Los Angeles: Sage Publications. 2017. https://doi.org/10.4135/9781071802878
  • White MD, Marsh EE. Content analysis: A flexible methodology. Libr Trends. 2006; 55(1):22-45. https://doi.org/10.1353/lib.2006.0053
  • Lytridis C, Vrochidou E, Sidiropoulos G, Papakostas GA, Kaburlasos VG, Kourampa E, Karageorgiou E. Audio Signal Recognition Based on Internals' Numbers (INs) Classification Techniques. In: 10th International Conference on Information, Intelligence, Systems and Applications. 2019; Patras, Greece. https://doi.org/10.1109/IISA.2019.8900749
  • Mavridis N. A review of verbal and non-verbal human-robot interactive communication. Rob Auton Syst. 2015; 63:22-30. https://doi.org/10.1016/j.robot.2014.09.031
  • Autism Speaks. Challenging behaviors tool kit. New York: Autism Speaks. 2012.
  • Clay RA. Women outnumber men in psychology, but not in the field's top echelons. Monitor on Psychology. 2017; 48(7):18-21. https://doi.org/10.1037/e509952018-001