Clinical Applications of Robots in Autism Spectrum Disorder Diagnosis and Treatment

  • Joshua J. Diehl
  • Charles R. Crowell
  • Michael Villano
  • Kristin Wier
  • Karen Tang
  • Laurel D. Riek

Abstract

Advances in socially assistive robotics have the potential to promote innovation in the diagnosis and treatment of individuals with Autism Spectrum Disorder (ASD). Research has revealed that individuals with ASD (1) show strengths in understanding the physical, object-related world and weaknesses in understanding the social world, (2) are more responsive to feedback given by a computer than a human, and (3) are more interested in treatment involving technology/robots. These findings suggest that a co-robot therapist may be an important addition to clinical assessment and/or therapy if it can emulate certain human therapist functions. Still, the majority of research in this area to date has focused on the development of technology, with scant attention paid to best practice clinical approaches. Therefore, the clinical use of robots for ASD should be considered an experimental approach to diagnosis and/or treatment until rigorous clinical trials are conducted and replicated. The end of this section includes a roadmap for future research on the clinical uses for robots in the diagnosis and treatment of individuals with ASD. Crucially, clinical innovation must parallel technological innovation if this approach is to become an accepted diagnostic and/or treatment approach for ASD.

References

  1. Barakova EI. Robots for social training of autistic children. Empowering therapists in intensive training programs. In: Abraham et al. editors. Proceedings of IEEE WICT 2011, pp. 14–19Google Scholar
  2. Bird G, Leighton J, Press C, Heyes C. Intact automatic imitation of human and robot actions in autism spectrum disorders. Proc Royal Society London: B. 2007;274:3027–31.CrossRefGoogle Scholar
  3. Dautenhahn K, Werry I. Towards interactive robots in autism therapy: background motivation, and challenges. Prag Cog. 2004;12:1–35.CrossRefGoogle Scholar
  4. Diehl JJ, Schmitt L, Crowell CR, Villano M. The clinical use of robots for children with autism spectrum disorders: a critical review. Res Aut Spect Dis. 2012;6:249–62.CrossRefGoogle Scholar
  5. Feil-Seifer D, Matarić MJ. Toward socially assistive robotics for augmenting interventions for children with autism spectrum disorders. Exp Robotics. 2009;54:201–10.CrossRefGoogle Scholar
  6. Feil-Seifer D, Matarić MJ. Using robots to augment (not replace) people in therapeutic settings. Refereed workshop: robotics: science and system; 2011; Los Angeles.Google Scholar
  7. Feil-Seifer D, Matarić MJ. Defining socially assistive robotics. International conference on rehabilitation robotics; 2005; Chicago. p. 465–8.Google Scholar
  8. François D, Powell S, Dautenhahn K. A long-term study of children with autism playing with a robotic pet: taking inspirations from non-directive play therapy to encourage children’s proactivity and initiative-taking. Int Studies. 2009;10:324–73.CrossRefGoogle Scholar
  9. Gillesen J, Barakova EI, Huskens BE, Feijs LM. From training to robot behavior: towards custom scenarios for robotics in training programs for ASD. IEEE Rehab Robotics. 2011; 387–93.Google Scholar
  10. Hollerback JM, Mason MT, Christensen HI. A roadmap for U.S. robotics – from internet to robotics. Updated 2009. http://wwww.us-robotics.us. Accessed 1 Mar 2012.
  11. Klin A, Jones W. Attributing social and physical meaning to ambiguous visual displays in individuals with higher-functioning autism spectrum disorders. Brain Cog. 2006;61:40–53.CrossRefGoogle Scholar
  12. Klin A, Jones W, Schultz R, Volkmar F, Cohen D. Visual fixation patterns during viewing of naturalistic social situations as predictors of social competence in individuals with autism. Arch Gen Psych. 2002;59:809–16.CrossRefGoogle Scholar
  13. Klin A, Lin DJ, Gorrindo P, Ramsay G, Jones W. Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature. 2009;459:257–61.PubMedCrossRefGoogle Scholar
  14. Lord C, Rutter M, DiLavore PC, Risi S. Autism diagnostic observation schedule. Los Angeles: Western Psychological Services; 1999.Google Scholar
  15. Lord C, Risi S, Lambrecht L, et al. Autism diagnostic observational schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Aut Dev Dis. 2000;30:205–23.CrossRefGoogle Scholar
  16. Lourens T, Barakova EI. User-friendly robot environment for creation of social scenarios. Found Nat Art Computation. 2011; LNCS 6686:212–21.CrossRefGoogle Scholar
  17. Lund HH, Pederson MD, Beck R. Modular robotic tiles: experiments for children with autism. Art Life Robotics. 2009;13:393–400.Google Scholar
  18. Ozonoff S. Reliability and validity of the wisconsin card sorting test in studies of autism. Neuropsychology. 1995;9:491–500. doi:10.1037/0894–4105.9.4.491.CrossRefGoogle Scholar
  19. Pierno AC, Mari M, Lusher D, Castiello U. Robotic movement elicits visuomotor priming in children with autism. Neuropsychologia. 2008;46:448–54.PubMedCrossRefGoogle Scholar
  20. Riek LD. Wizard of oz studies in HRI: a systematic review and new reporting guidelines. J Hum Robot Int. 2012;1:119–136CrossRefGoogle Scholar
  21. Robins B, Dickerson P, Stribling P, Dautenhahn K. Robot-mediated joint attention in children with autism: a case study in robot-human interaction. Int Studies. 2004;5:161–98.CrossRefGoogle Scholar
  22. Robins B, Dautenhahn K, te Boekhorst R, Billard A. Robotic assistants in therapy and education of children with autism: can a small humanoid robot encourage social interaction skills? Univ Access Inform Soc. 2005;4:115–20.Google Scholar
  23. Robins B, Dautenhahn K, Dubowski J. Does appearance matter in the interaction of children with autism with a humanoid robot? Int Studies. 2006;7:509–12.CrossRefGoogle Scholar
  24. Rogers SJ, Vismara LA. Empirically supported comprehensive treatments for early autism. J Clin Child Adolesc Psychol. 2008;37:8–38.PubMedCrossRefGoogle Scholar
  25. Scassellati B. How social robots will help us diagnose, treat, and understand autism. Robotics Res. 2007;28:552–63.CrossRefGoogle Scholar
  26. Stribling P, Rae J, Dickerson P. Using conversation analysis to explore the recurrence of a topic in the talk of a boy with autism spectrum disorder. Clin Ling Phon. 2009;23:555–82.CrossRefGoogle Scholar
  27. Tapus A, Matarić M, Scassellati B. The grand challenges in socially assistive robotics. IEEE Robotics Automat Mag. 2007;4:35–42.CrossRefGoogle Scholar
  28. Villano M, Crowell CR, Wier K, et al. DOMER: A wizard of oz interface for using interactive robots to scaffold social skills for children with autism spectrum disorders. ACM/IEEE international conference on human-robot interaction; 2011. p. 279–80.Google Scholar
  29. Wainer J, Ferrari E, Dautenhahn K, Robins B. The effectiveness of using a robotics class to foster collaboration among groups of children with autism in an exploratory study. Personal Ubiq Comput. 2010;14:445–55.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Joshua J. Diehl
    • 1
  • Charles R. Crowell
    • 2
  • Michael Villano
    • 3
  • Kristin Wier
    • 4
  • Karen Tang
    • 5
  • Laurel D. Riek
    • 6
  1. 1.Department of PsychologyUniversity of Notre DameNotre DameUSA
  2. 2.Department of PsychologyUniversity of Notre DameNotre DameUSA
  3. 3.Department of PsychologyUniversity of Notre DameNotre DameUSA
  4. 4.Sonya Ansari Center for AutismSouth BendUSA
  5. 5.Department of PsychologyUniversity of Notre DameNotre DameUSA
  6. 6.Department of Computer Science and EngineeringUniversity of Notre DameNotre DameUSA

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