A Collaborative Patient-Carer Interface for Generating Home Based Rules for Self-Management

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8456)


The wide spread prevalence of mobile devices, the decreasing costs of sensor technologies and increased levels of computational power have all lead to a new era in assistive technologies to support persons with Alzheimer’s disease. There is, however, still a requirement to improve the manner in which the technology is integrated into current approaches of care management. One of the key issues relating to this challenge is in providing solutions which can be managed by non-technically orientated healthcare professionals. Within the current work efforts have been made to develop and evaluate new tools with the ability to specify, in a non-technical manner, how the technology within the home environment should be monitored and under which conditions an alarm should be raised. The work has been conducted within the remit of a collaborative patient-carer system to support self-management for dementia. A visual interface has been developed and tested with 10 healthcare professionals. Results following a post evaluation of system usability have been presented and discussed.


Self-management Visual interface Dementia Home based monitoring 



Invest Northern Ireland is acknowledged for supporting this project under the R and D grant RD0513844.


  1. 1.
    Jonsdottir, H.: Self-management programmes for people living with chronic obstructive pulmonary disease: a call for a reconceptualisation. J. Clin. Nurs. 22, 621–637 (2013)CrossRefGoogle Scholar
  2. 2.
    McCullagh, P., et al.: Promoting behavior change in long term conditions using a self-management platform. In: Langdon, P.M., Clarkson, P.J., Robinson, P. (eds.) Designing Inclusive Interactions, pp. 229–238. Springer, London (2010)CrossRefGoogle Scholar
  3. 3.
    Zheng, H., et al.: Smart self-management: assistive technology to support people with chronic disease. J. Telemed. Telecare 16, 224–227 (2010)CrossRefGoogle Scholar
  4. 4.
    Martin, F., et al.: Conceptualisation of self-management intervention for people with early stage dementia. Eur. J. Ageing 10, 75–87 (2013)CrossRefGoogle Scholar
  5. 5.
    Mason, S., et al.: Electronic reminding technology for cognitive impairment. Br. J. Nurs. 21(14), 855 (2012)CrossRefGoogle Scholar
  6. 6.
    Morris, M.E., et al.: Smart-home technologies to assist older people to live well at home. J. Aging Sci. 1. 101 (2013)Google Scholar
  7. 7.
    Chang, A.Y., Han-Chen, H., Dwen-Ren, T.: Development of practical smart house scenario control system. Przegląd Elektrotechniczny 89, 159–161 (2013)Google Scholar
  8. 8.
    Catala, A., et al.: A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance. Sci. Comput. Programm. 78(10), 1930–1950 (2013)CrossRefGoogle Scholar
  9. 9.
    National Instruments: Labview.
  10. 10.
    McGrath, M.J., Terrance, J.D.: A common personal health research platform. Intel Technol. J. 13(3), 122–147 (2009)Google Scholar
  11. 11.
    Wolber, D., et al.: App Inventor. O’Reilly Media Inc, Sebastopol (2011)Google Scholar
  12. 12.
    Beckmann, C., Anind, D.: Siteview: Tangibly programming active environments with predictive visualization. In: Adjunct Proceedings of UbiComp (2003)Google Scholar
  13. 13.
    Sohn, T., Anind, D.: iCAP: an informal tool for interactive prototyping of context-aware applications. In: CHI’03 Extended Abstracts on Human Factors in Computing Systems. ACM (2003)Google Scholar
  14. 14.
    Bonino, D., Corno, F., De Russis, L.: A user-friendly interface for rules composition in intelligent environments. In: Novais, P., Preuveneers, D., Corchado, J.M. (eds.) ISAmI 2011. AISC, vol. 92, pp. 213–217. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Hong, X., et al.: Open Home: approaches to constructing sharable datasets within Smart Homes. In: CHI 2009 workshop on developing shared home behavior datasets to advance HCI and ubiquitous computing, 4 April 2009Google Scholar
  16. 16.
    Nugent, C.D., et al.: HomeCI-A visual editor for healthcare professionals in the design of home based care. In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007. IEEE (2007)Google Scholar
  17. 17.
    McDonald, H.A., Nugent, C.D., Hallberg, J., Finlay, D.D., Moore, G.: homeRuleML version 2.1: A revised and extended version of the homeRuleML concept. In: Roa Romero, L.M. (ed.) XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. IFMBE Proceedings, vol. 42, pp. 1243–1246. Springer, Heidelberg (2014)Google Scholar
  18. 18.
    Nugent, C.D., Finlay, D.D., Davies, R.J., Wang, H.Y., Zheng, H., Hallberg, J., Synnes, K., Mulvenna, M.D.: homeML – An open standard for the exchange of data within smart environments. In: Okadome, T., Yamazaki, T., Makhtari, M. (eds.) ICOST. LNCS, vol. 4541, pp. 121–129. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Computer Science Research Institute and School of Computing and MathematicsUniversity of UlsterNewtownabbeyUK
  2. 2.Department of Computer Science, Electrical and Space EngineeringLuleå University of TechnologyLuleåSweden
  3. 3.Ubiquitous Computing LaboratoryKyung Hee UniversitySeocheon-dong, Giheung-guSouth Korea

Personalised recommendations