10.1145/3308561.3353784acmconferencesArticle/Chapter ViewAbstractPublication PagesassetsConference Proceedings
research-article

CHIMELIGHT: Augmenting Instruments in Interactive Music Therapy for Children with Neurodevelopmental Disorders

ABSTRACT

In this paper, we propose a new mobile system to support therapists for teaching and tracking socio-communicative behaviors in children with neurodevelopmental disorders during music therapy sessions. The CHIMELIGHT system was designed to deal with the current issues in conventional therapies, such as the difficulty in both evaluating the performance and maintaining engagement of these children during therapeutic activities. The system evaluated movements made by a child with neurodevelopmental disorders playing a musical instrument while delivering contingent visual feedback based on real-time motion analysis. A set of metrics was implemented to evaluate the performance during the therapy activity and quantify specific target behaviors. An evaluation study performed during music therapy group sessions showed that the CHIMELIGHT-delivered visual feedback increased the engagement of children in the activity and decreased targeted negative behaviors. In some participants, we observed potential changes in their positive behaviors. Interviews and questionnaires provided to therapists showed that the developed system was effective for supporting evidence-based music therapy. Accordingly, our research enables new methods for both interactive therapy and mediation of the interaction between therapists and children with neurodevelopmental disorders.

References

  1. Vera Bernard-Opitz, N. Sriram, and Sharul Sapuan. 1999. Enhancing vocal imitations in children with autism using the IBM SpeechViewer. Autism 3, 2: 131--147.Google ScholarGoogle ScholarCross RefCross Ref
  2. John Brooke. 1996. SUS: A quick and dirty usability scale. In Usability Evaluation in Industry, P. W. Jordan, B. Thomas, B. A. Weerdmeester, and A. L. McClelland (eds.). London: Taylor and Francis, UK, 194: 189--194.Google ScholarGoogle Scholar
  3. Franceli L. Cibrian, Oscar Pena, Deysi Ortega, and Monica Tentori. 2017. BendableSound: An elastic multisensory interface using touch-based interactions to assist children with severe autism during music therapy. International Journal of Human-Computer Studies 0, 1--16.Google ScholarGoogle Scholar
  4. Lisa M. Gallagher and Anita L. Steele. 2001. Developing and using a computerized database for music therapy in palliative medicine. Journal of Palliative Care 17, 3: 147--154.Google ScholarGoogle Scholar
  5. Monika Geretsegger, Cochavit Elefant, Karin A. Mössler, and Christian Gold. 2014. Music therapy for people with autism spectrum disorder. Cochrane Database of Systematic Reviews 6, Art. No.: CD004381.Google ScholarGoogle Scholar
  6. Avi Gilboa. 2007. Testing MAP: A graphic method for describing and analyzing music therapy sessions. The Arts in Psychotherapy 34, 4:309--320.Google ScholarGoogle ScholarCross RefCross Ref
  7. Nicole D. Hahna, Susan Hadley, Vern H. Miller, and Michelle Bonaventura. 2012. Music technology usage in music therapy: A survey of practice. The Arts in Psychotherapy 39, 456--464.Google ScholarGoogle ScholarCross RefCross Ref
  8. Joshua Hailpern. 2007. Encouraging Speech and Vocalization in Children with Autistic Spectrum Disorder. In Proceedings of the ACM SIGACCESS Accessibility and Computing (ASSETS'07), 89, 47--52.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Joshua Hailpern, Andrew Harris, Reed La Botz, Brianna Birman, and Karrie Karahalios. 2012. Designing Visualizations to Facilitate Multisyllabic Speech with Children with Autism and Speech Delays. In Proceedings of the Designing Interactive Systems Conference, 126--135.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Yuka Ishizuka and Junichi Yamamoto. 2016. Contingent imitation increases verbal interaction in children with autism spectrum disorders. Autism 20, 8, 1011--1020.Google ScholarGoogle ScholarCross RefCross Ref
  11. Amy Kalas. 2012. Joint attention responses of children with autism spectrum disorder to simple versus complex music. Journal of Music Therapy 49, 4, 430--452.Google ScholarGoogle ScholarCross RefCross Ref
  12. Colin Lee. 2000. A method of analyzing improvisations in music therapy. Journal of music therapy 37, 2, 147--167.Google ScholarGoogle ScholarCross RefCross Ref
  13. Hayoung A. Lim. 2012. Developmental Speech-Language Training through Music for Children with Autism Spectrum Disorders. London and Philadelphia: Jessica Kingsley Publishers.Google ScholarGoogle Scholar
  14. Hayoung A. Lim and Ellary Draper. 2011. The effects of music therapy incorporated with applied behavior analysis verbal behavior approach for children with autism spectrum disorders. Journal of Music Therapy 48, 4, 532--550.Google ScholarGoogle ScholarCross RefCross Ref
  15. Joana Lobo and Kenji Suzuki. 2018. Designing Social Playware Mediated Communication with Contingent Feedback Devices. In Proceedings of the ACM Conference Companion Publication on Designing Interactive Systems (DIS18), 93--97.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Geoff Luck, Olivier Lartillot, Jaakko Erkkilä, Petri Toiviainen, and Kari Riikkilä. 2009. Predicting Music Therapy Clients' Type of Mental Disorder Using Computational Feature Extraction and Statistical Modelling Techniques. Communications in Computer and Information Science 37, 156--167.Google ScholarGoogle ScholarCross RefCross Ref
  17. Henrik H. Lund and Tumi Thorsteinsson. 2012. Social playware for mediating tele-play interaction over distance. Artificial Life and Robotics 16, 4, 435--440.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Wendy L. Magee (Ed.). 2014. Music Technology in Therapeutic and Health Settings. London: Jessica Kingsley Publishers.Google ScholarGoogle Scholar
  19. Richard A. Magill. 1998. Motor Learning Concepts and Applications. Boston: McGraw-Hill.Google ScholarGoogle Scholar
  20. John McGowan, Grégory Leplâtre, and Iain McGregor. 2017. CymaSense: A Novel Audio-Visual Therapeutic Tool for People on the Autism Spectrum. In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17), 62--71.Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. François Michaud and Catherine Théberge-Turmel. 2002. Mobile Robotic Toys and Autism. In Socially Intelligent Agents - Creating Relationships with Computers and Robots. Springer, 125--132.Google ScholarGoogle Scholar
  22. Eric B. Miller. 2011. Bio-Guided Music Therapy: A Practitioner's Guide to the Clinical Integration of Music and Biofeedback. London: Jessica Kingsley Publishers.Google ScholarGoogle Scholar
  23. Narcís Parés, Anna Carreras, Jaume Durany, Jaume Ferrer, Pere Freixa, David Gomez, Orit Kruglanski, Roc Parés, Ignasi Ribas, Miquel Soler, and Alex Sanjurjo. 2005. Promotion of creative activity in children with severe autism through visuals in an interactive multisensory environment. In Proceedings of the conference on Interaction design and children, Colorado, 110--116.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Alaine E. Reschke-Hernández. 2011. History of music therapy treatment interventions for children with autism. Journal of Music Therapy 48, 2, 169--207.Google ScholarGoogle ScholarCross RefCross Ref
  25. Rebecca Schnall, Hwayoung Cho, and Jianfang Liu. 2018. Health Information Technology Usability Evaluation Scale (Health-ITUES) for Usability Assessment of Mobile Health Technology: Validation Study. JMIR Mhealth Uhealth 6, 1, e4.Google ScholarGoogle ScholarCross RefCross Ref
  26. SkoogMusic. Skoogmusic | We create music technology that lets anyone make music. Retrieved June, 2019 from http://www.skoogmusic.com/.Google ScholarGoogle Scholar
  27. Stoyan R. Stoyanov, Leanne Hides, David J. Kavanagh, and Hollie Wilson. 2016. Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS). JMIR Mhealth Uhealth 4, 2, e72.Google ScholarGoogle ScholarCross RefCross Ref
  28. Lilia Villafuerte, Milena Markova, and Sergi Jorda. 2012. Acquisition of social abilities through musical tangible user interface. In CHI '12 Extended Abstracts on Human Factors in Computing Systems (CHI EA '12), 745--760.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Thomas Wosch and Tony Wigram. 2007. Microanalysis in Music Therapy: Methods, Techniques and Applications for Clinicians, Researchers, Educators and Students. Jessica Kingsley Publishers.Google ScholarGoogle Scholar

Index Terms

  1. CHIMELIGHT: Augmenting Instruments in Interactive Music Therapy for Children with Neurodevelopmental Disorders

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader
          About Cookies On This Site

          We use cookies to ensure that we give you the best experience on our website.

          Learn more

          Got it!