An ambient assisted living system for dementia patients

Dementia is a major health and social care challenge of today and the near future as a result of increasedhuman lifespan. Currently, there is no therapeutic solution for dementia, but a solution for managing the wanderingbehavior of dementia patients can be provided by an ambient assisted living system. In this paper, the design andimplementation of iCarus, which is an intelligent ambient assisted living system for dealing with wandering behaviorin early stages of dementia, is described. The aim of iCarus is to provide independent living for elderly people anda cost-effective way of monitoring them. iCarus is a zone-based system that forms a safety net. When a wanderingepisode occurs, rule-based context reasoning is employed to determine the actions that are to be executed. These actionsinclude warning the patient, navigating the patient to his home, sending notifications to the caregiver(s), and initiatinga real-time tracking session for the caregiver and the emergency service. Also, caregivers are able to construct their ownrules and extend the functionality of the system according to their own needs. Constructing new rules is done by aninnovative user interface. As a case study, iCarus is described and evaluated with a scenario. In order to evaluate theusability of iCarus, a questionnaire was administered after the users tried the system. The results were then statisticallyanalyzed and reported.

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[1] Prince M, Comas-Herrera A, Knapp M, Guerchet M, Karagiannidou M. World Alzheimer Report 2016: Improving Healthcare for People Living with Dementia: Coverage, Quality and Costs Now and in the Future. Technical Report 2016. London, UK: Alzheimer’s Disease International, 2016.
[2] Alzheimer’s Disease Education and Referral Center. Alzheimer’s Disease Fact Sheet. Technical Report 2010: NIH Publication No. 08-6423. Silver Spring, MD, USA: National Institutes of Health, 2010.
[3] Sposaro F, Danielson J, Tyson G. iWander: An Android application for dementia patients. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology; 2010. pp. 3875-3878.
[4] Wan J, Byrne CA, O’Grady MJ, O’Hare GMP. Managing wandering risk in people with dementia. IEEE T HumMach Syst 2015; 45: 819-823.
[5] Cipriani G, Lucetti C, Nuti A, Danti S. Wandering and dementia. Psychogeriatrics 2014; 14: 135-142.
[6] Algase DL, Moore DH, Vandeweerd C, Gavin-Dreschnack DJ. Mapping the maze of terms and definitions in dementia-related wandering. Aging Ment Health 2007; 11: 686-698.
[7] Hoey J, Yang X, Quintana E, Favela J. LaCasa: Location and context-aware safety assistant. In: 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops; 2012. pp. 171-174.
[8] Wan J, Byrne C, O’Hare GMP, O’Grady MJ. Orange alerts: Lessons from an outdoor case study. In: 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops; 2011. pp. 446-451.
[9] Weiser M. The computer for the 21st century. Sci Am 1991; 265: 94-104.
[10] Remagnino P, Foresti GL. Ambient intelligence: a new multidisciplinary paradigm. IEEE T Syst Man Cy A Jan 2005; 35: 1-6.
[11] Wan J, Byrne C, O’Hare GMP, O’Grady MJ. OutCare: Supporting dementia patients in outdoor scenarios. In: Setchi R, Jordanov I, Howlett RJ, Jain LC, editors. Knowledge-Based and Intelligent Information and Engineering Systems. Berlin, Germany: Springer, 2010. pp. 365-374.
[12] Cook DJ, Augusto JC, Jakkula VR. Ambient intelligence: technologies, applications, and opportunities. Pervasive Mob Comput 2009; 5: 277-298.
[13] Kleinberger T, Becker M, Ras E, Holzinger A, Müller P. Ambient intelligence in assisted living: enable elderly people to handle future interfaces. In: Stephanidis C, editor. Universal Access in Human-Computer Interaction. Ambient Interaction. Berlin, Germany: Springer, 2007. pp. 103-112.
[14] Kumar A, Ma M, Lau CT, Chan S. A framework of real-time wandering management for person with dementia. In: Proceedings of the 8th International Conference on Computer Modeling and Simulation; 2017. pp. 146-150.
[15] Rodriguez MD, Navarro RF, Favela J, Hoey J. An ontological representation model to tailor ambient assisted interventions for wandering. In: AAAI Fall Symposium: Artificial Intelligence for Gerontechnology; 2012.
[16] Lin Q, Zhang D, Chen L, Ni H, Zhou X. Managing elders’ wandering behavior using sensors-based solutions: a survey. Int J Gerontol 2014; 8: 49-55.
[17] Blackburn P. Freedom to wander. Nurs Times 1988; 84: 54-55.
[18] Miskelly F. A novel system of electronic tagging in patients with dementia and wandering. Age Ageing 2004; 33: 304-306.
[19] Parikh S, Stirman K. Schema design for time series data in mongodb. 2014. https://www.mongodb.com/blog/post/ schema-design-for-time-series-data-in-mongodb.
[20] Lekeu F, Wojtasik V, van der Linden M, Salmon E. Training early Alzheimer patients to use a mobile phone. Acta Neurol Belg 2002; 102: 114-121.
[21] Fisk AD, Czaja SJ, Rogers WA, Charness N, Czaja SJ, Sharit J. Designing for Older Adults: Principles and Creative Human Factors Approaches. Boca Raton, FL, USA: CRC Press, 2009.
[22] Miskelly F. Electronic tracking of patients with dementia and wandering using mobile phone technology. Age Ageing 2005; 34: 497-499.
[23] Heard K, Watson TS. Reducing wandering by persons with dementia using differential reinforcement. J Appl Behav Anal 1999; 32: 381-384.
[24] Gruber TR. A translation approach to portable ontology specifications. Knowl Acquis 1993; 5: 199-220.
[25] Gu T, Wang XH, Pung HK, Zhang DQ. An ontology-based context model in intelligent environments. In: Proceedings of Communication Networks and Distributed Systems Modeling and Simulation Conference; 2004. pp. 270-275.
[26] Hervás R, Bravo J, Fontecha J. A context model based on ontological languages: a proposal for information visualization. J Univers Comput Sci 2010; 16: 1539-1555.
[27] Kim E, Choi J. An ontology-based context model in a smart home. In: International Conference on Computational Science and Its Applications; 2006; Berlin, Germany: Springer. pp. 11-20.
[28] Mitchell M, Meyers C, Wang AIA, Tyson G. Contextprovider: Context awareness for medical monitoring applications. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2011. pp. 5244-5247.
[29] Wang XH, Zhang DQ, Gu T, Pung HK. Ontology based context modeling and reasoning using OWL. In: Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops; 2004. pp. 18-22.
[30] Nielsen J. Usability Engineering. San Diego, CA, USA: Academic Press, 1993.
[31] Kline P. The Handbook of Psychological Testing. 2nd ed. London, UK: Routledge, 2000.
[32] Norman G. Likert scales, levels of measurement and the “laws” of statistics. Adv Health Sci Educ Theory Pract 2010; 15: 625-632.
[33] Weaver KF, Morales V, Dunn SL, Godde K, Weaver, PF. Mann-Whitney U and Wilcoxon signed-rank. In: Weaver KF, Morales V, Dunn SL, Godde K, Weaver, PF, editors. An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences. New York, NY, USA: John Wiley & Sons, 2017.