Ontological User Modeling for Ambient Assisted Living Service Personalization
Given that the population is aging, it is crucial to develop technologies which will not only help the elderly to age in place, but also live in place with independent and healthy lifestyle. Ambient Assisted Living (AAL) environments can help the elderly and people with functional diversity by anticipating their needs in specific situations and acting proactively in order to properly assist them in performing their activities of daily living (ADLs). Since the users needs tend to be very diverse in regard to functioning and disability levels, it is crucial to have personalized services capable of providing tailored assistance to a user based on their unique preferences, requirements, and desires. This paper introduces the ontology named AATUM (Ambient Assistive Technology User Model), to be adopted by systems whose goal is to enhance user quality of life within ALL environments through service personalization. Its main feature is the use of The International Classification of Functioning, Disability and Health (ICF) to model the user’s functioning and disability levels in a consistent and internationally comparable way. The use of the proposed ontology is illustrated through its application in two different case studies.
KeywordsOntology Context-aware Functioning User centered World Health Organization
This research work has been funded by the CAPES PROCAD project (071/2013), whose support is gratefully acknowledged.
- 1.Bhowmick, P.K., Sarkar, S., Basu, A.: Ontology based user modeling for personalized information access. IJCSA 7(1), 1–22 (2010)Google Scholar
- 2.Centers for Disease Control and Prevention (CDC): The State of Aging and Health in America 2013. US Department of Health and Human Services, Centers for Disease Control and Prevention, Atlanta (2013)Google Scholar
- 3.Fredrich, C., Kuijs, H., Reich, C.: An ontology for user profile modelling in the field of ambient assisted living. In: Sixth International Conferences on Advanced Service Computing, SERVICE COMPUTATION 2014, pp. 24–31 (2014)Google Scholar
- 5.Heckmann, D., Schwartz, T., Brandherm, B., Schmitz, M., von Wilamowitz-Moellendorff, M.: Gumo – the general user model ontology. In: Ardissono, L., Brna, P., Mitrovic, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 428–432. Springer, Heidelberg (2005). https://doi.org/10.1007/11527886_58CrossRefGoogle Scholar
- 7.Kadouche, R., Mokhtari, M., Giroux, S., Abdulrazak, B.: Personalization in smart homes for disabled people. In: Second International Conference on Future Generation Communication and Networking, FGCN 2008, vol. 2, pp. 411–415. IEEE (2008)Google Scholar
- 9.Noy, N.F., McGuinness, D.L., et al.: Ontology development 101: a guide to creating your first ontology (2001)Google Scholar
- 10.World Health Organization: International classification of functioning, disability and health: ICF. World Health Organization (2001)Google Scholar
- 11.World Health Organization: International classification of diseases (ICD) (2012). http://www.who.int/classifications/icd/en/. Retrieved June 2015
- 13.Rusu, L., Cramariuc, B.: A conceptual approach for innovative home care solution. J. Appl. Comput. Sci. Math. 17(17), 22–26 (2014)Google Scholar
- 15.Skillen, K.-L., Chen, L., Nugent, C.D., Donnelly, M.P., Burns, W., Solheim, I.: Ontological user profile modeling for context-aware application personalization. In: Bravo, J., López-de-Ipiña, D., Moya, F. (eds.) UCAmI 2012. LNCS, vol. 7656, pp. 261–268. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35377-2_36CrossRefGoogle Scholar
- 16.Sutterer, M., Droegehorn, O., David, K.: UPOS: User profile ontology with situation-dependent preferences support. In: First International Conference on Advances in Computer-Human Interaction, pp. 230–235. IEEE (2008)Google Scholar
- 17.Üstün, T.B.: Measuring Health and Disability: Manual for WHO Disability Assessment Schedule WHODAS 2.0. World Health Organization, Geneva (2010)Google Scholar