skip to main content
10.1145/2896338.2896352acmotherconferencesArticle/Chapter ViewAbstractPublication PagesdhConference Proceedingsconference-collections
research-article

Computer-Supported Assessment for Tailoring Assistive Technology

Published:11 April 2016Publication History

ABSTRACT

The main purpose of assistive technology is to support an individual's daily activities, in order to increase ability, autonomy, relatedness and quality of life. The aim for the work presented in this article is to develop automated methods to tailor the behavior of the assistive technology for the purpose to provide just-in-time, adaptive interventions targeting multiple domains. This requires methods for representing and updating the user model, including goals, preferences, abilities, activity and its situation. We focus the assessment and intervention tasks typically performed by therapists and provide knowledge-based technology for supporting the process. A formative evaluation study was conducted as a part of a participatory action research process, involving two rehabilitation experts, two young individuals and one senior individual as end-user participants, in addition to knowledge engineers. The main contribution of this work is a theory-based method for assessing the individual's goals, preferences, abilities and motives, which is used for building a holistic user model. The user model is continuously updated and functions as the base for tailoring the system's assistive behavior during intervention and follow-up.

References

  1. G. Andrews, R. Poulton, and G. Skoog. Lifetime risk of depression: restricted to a minority or waiting for most? The British Journal of Psychology, 187:495--496, December 2005.Google ScholarGoogle ScholarCross RefCross Ref
  2. R. Annicchiarico, F. Campana, A. Federici, C. Barrué, U. Cortés, A. Villar, and C. Caltagirone. Using scenarios to draft the support of intelligent tools for frail elders in the share-it approach. In Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence, IWANN '09, pages 635--641, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Baskar and H. Lindgren. Towards Personalised Support for Monitoring and Improving Health in Risky Environments. In VIII Workshop on Agents Applied in Health Care (A2HC), pages 93--104, 2013.Google ScholarGoogle Scholar
  4. J. Baskar and H. Lindgren. Cognitive architecture of an agent for human-agent dialogues. In PAAMS (Workshops), volume 430 of Communications in Computer and Information Science, pages 89--100. Springer, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  5. J. Baskar and H. Lindgren. Human-agent dialogues on health topics - an evaluation study. In J. Bajo, K. Hallenborg, P. Pawlewski, V. Botti, N. Sánchez-Pi, D. N. Duque Méndez, F. Lopes, and V. Julian, editors, Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection: International Workshops of PAAMS 2015, Salamanca, Spain, June 3-4, 2015. Proceedings, volume 430 of Communications in Computer and Information Science, pages 28--39. Springer International Publishing, 2015.Google ScholarGoogle Scholar
  6. R. Cáceres and A. Friday. Ubicomp systems at 20: Progress, opportunities, and challenges. IEEE Pervasive Computing, 11(1):14--21, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. F. Carmagnola, F. Cena, and C. Gena. User model interoperability: a survey. User Modeling and User-Adapted Interaction, 21(3):285--331, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. C. I. Chesñevar, J. McGinnis, S. Modgil, I. Rahwan, C. Reed, G. R. Simari, M. South, G. Vreeswijk, and S. Willmott. Towards an argument interchange format. Knowledge Eng. Review, 21(4):293--316, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. I. Gómez-Sebastià, D. Garcia-Gasulla, C. Barrué, J. Vázquez-Salceda, and U. Cortés. A flexible agent-oriented solution to model organisational and normative requirements in assistive technologies. In Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence, pages 79--88, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. E. Guerrero, H. Lindgren, and J. C. Nieves. ALI, an Ambient Assisted Living System for Supporting Behavior Change. In VIII Workshop on Agents Applied in Health Care (A2HC 2013), pages 81--92, 2013.Google ScholarGoogle Scholar
  11. E. Guerrero, J. C. Nieves, and H. Lindgren. Activity qualifiers in an argumentation framework as instruments for agents when evaluating human activity. 2016. To appear.Google ScholarGoogle Scholar
  12. E. Guerrero, J. C. Nieves, and H. Lindgren. An Activity-Centric Argumentation Framework for Assistive Technology Aimed at Improving Health. Argument & Computation, 2016. To appear.Google ScholarGoogle ScholarCross RefCross Ref
  13. D. Isern, D. Sánchez, and A. Moreno. Agents applied in health care: A review. I. J. Medical Informatics, 79(3):145--166, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  14. R. Kadouche, M. Mokhtari, S. Giroux, and B. Abdulrazak. Personalization in smart homes for disabled people. In Proceedings of the 2008 Second International Conference on Future Generation Communication and Networking - Volume 02, FGCN '08, pages 411--415, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. V. Kaptelinin. Computer-mediated activity: Functional organs in social and developmental contexts. In B. Nardi, editor, Context and Consciousness. Activity Theory and Human Computer Interaction, pages 45--68. MIT Press, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. M. Kennedy, J. Powell, T. H. Payne, J. Ainsworth, A. Boyd, and I. Buchan. Active assistance technology for health-related behavior change: An interdisciplinary review. Journal of Medical Internet Research, 14(3):e80, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  17. G. Kielhofner. A model of human occupation. Lippincott, Williams & Wilkins, 2008.Google ScholarGoogle Scholar
  18. A. Kobsa. Generic user modeling systems. User Modeling and User-Adapted Interaction, 11(1--2):49--63, Mar. 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. T. Kuflik, J. Kay, and B. Kummerfeld. Challenges and solutions of ubiquitous user modeling. In Ubiquitous Display Environments, pages 7--30. Springer, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  20. H. Lindgren, L. Lundin-Olsson, P. Pohl, and M. Sandlund. End users transforming experiences into formal information and process models for personalised health interventions. Studies In Health Technology And Informatics, 205:378--82, 2014.Google ScholarGoogle Scholar
  21. H. Lindgren and I. Nilsson. Towards user-authored agent dialogues for assessment in personalised ambient assisted living. International Journal of Web Engineering and Technology, 8(2):154--176, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. H. Lindgren, D. Surie, and I. Nilsson. Agent-supported assessment for adaptive and personalized ambient assisted living. In J. M. Corchado, J. Pérez Bajo, K. Hallenborg, P. Golinska, and R. Corchuelo, editors, Trends in Practical Applications of Agents and Multiagent Systems, volume 90 of Advances in Intelligent and Soft Computing, pages 25--32. Springer Berlin Heidelberg, 2011.Google ScholarGoogle Scholar
  23. H. Lindgren and P. Winnberg. A model for interaction design of personalised knowledge systems in the health domain. In M. Szomszor and P. Kostkova, editors, eHealth, volume 69 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pages 235--242. Springer, 2010.Google ScholarGoogle Scholar
  24. H. Lindgren, P. J. Winnberg, and P. Winnberg. Domain experts tailoring interaction to users - an evaluation study. In P. Campos, T. C. N. Graham, J. A. Jorge, N. J. Nunes, P. A. Palanque, and M. Winckler, editors, INTERACT (3), volume 6948 of Lecture Notes in Computer Science, pages 644--661. Springer, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. H. Lindgren and C. Yan. ACKTUS: A platform for developing personalized support systems in the health domain. In Proceedings of the 5th International Conference on Digital Health 2015, DH '15, pages 135--142, New York, NY, USA, 2015. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. J. McKay and P. Marshall. The dual imperatives of action research. Information Technology and People, 14(1):46--59, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  27. T. Ngandu and et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. The Lancet, 385(9984):2255--2263, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  28. J. C. Nieves, D. Surie, and H. Lindgren. Modeling actions based on a situative space model for recognizing human activities. In A. Ramsay and G. Agre, editors, AIMSA, volume 7557 of Lecture Notes in Computer Science, pages 266--275. Springer, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. H. Oinas-Kukkonen. Behavior change support systems: a research model and agenda. In Proceedings of the 5th international conference on Persuasive Technology, PERSUASIVE'10, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. M. Prince, A. Wimo, M. Guerchet, G.-C. Ali, Y.-T. Wu, and M. Prina. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. World Alzheimer Report, 2015.Google ScholarGoogle Scholar
  31. Y. Rogers. Moving on from weiser's vision of calm computing: Engaging ubicomp experiences. In P. Dourish and A. Friday, editors, Ubicomp, volume 4206 of Lecture Notes in Computer Science, pages 404--421. Springer, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. R. M. Ryan and E. L. Deci. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1):68--78, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  33. A. Seyfang, S. Miksch, M. Marcos, J. Wittenberg, C. Polo-Conde, and K. Rosenbrand. Bridging the gap between informal and formal guideline representations. In Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy, pages 447--451, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. D. Surie, H. Lindgren, and A. Qureshi. Kitchen as-a-pal: Exploring smart objects as containers, surfaces and actuators. In Ambient Intelligence-Software and Applications, pages 171--178. Springer, 2013.Google ScholarGoogle Scholar
  35. D. Sutton, P. Taylor, and K. Earle. Evaluation of proforma as a language for implementing medical guidelines in a practical context. BMC Medical Informatics and Decision Making, 6(1):20, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  36. M. Tateno, T. Park, T. Kato, W. Umene-Nakano, and T. Saito. Hikikomori as a possible clinical term in psychiatry: a questionnaire survey. BMC Psychiatry, 12(1), 2012.Google ScholarGoogle Scholar
  37. The Swedish National Board of Health and Welfare. Young people's medication, 2012.Google ScholarGoogle Scholar
  38. The Swedish National Board of Health and Welfare. Young people's health, 2013.Google ScholarGoogle Scholar

Index Terms

  1. Computer-Supported Assessment for Tailoring Assistive Technology

                    Recommendations

                    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