Advertisement

Towards an Evidence-Based and Context-Aware Elderly Caring System Using Persuasive Engagement

  • Yu Chun Yen
  • Ching Hu Lu
  • Yi Chung Cheng
  • Jing Siang Chen
  • Li Chen Fu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6767)

Abstract

Due to the rapid growth of the aging population, numerous countries have been attaching importance to establishing the well-being of the elderly. However, long-term healthcare is labor intensive. To alleviate the possible social costs associated with manpower and physical resources, we propose an evidence-based caring system which can inconspicuously and automatically monitor the health status of the elderly by continuously analyzing their real-life long-term living patterns deduced from activity recognition. In this way, caregivers can get hold of the behavior changes even the elderly is not under caregivers’ supervision. Moreover, we adopt a persuasive policy to provide timely reminders and encourage the elderly to achieve a healthier life. In the primary stage, we do preliminary experiments in a nursing room. Based on the experiment, we conduct several interviews aiming to improve our system in the next phase.

Keywords

Context-aware persuasive technology elderly healthcare 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Seo, K.-H., Oh, C., Choi, T.-Y., Lee, J.-J.: Bed-type Robotic System for the Bedridden. In: International Conference on Advanced Intelligent Mechatronics, California, USA (2005)Google Scholar
  2. 2.
    Howell Jones, M., Arcelus, A., Goubran, R., Knoefel, F.: A Pressure Sensitive Home Environment. In: IEEE International Workshop on Haptic Audio Visual Environments and their Applications, Canada (2006)Google Scholar
  3. 3.
    Huang, J.H., Hsia, C.C., Chuang, C.C.: A Behavior Mining Method by Visual Features and Activity Sequences in Institution-based Care. In: ICBME (2008)Google Scholar
  4. 4.
    Chou, C.T., Li, J.-Y., Fu, L.C.: Multi-robot Cooperation Based Human Tracking System Using Laser Range Finder. In: IEEE International Conference on Robotics and Automation (2011)Google Scholar
  5. 5.
    Data Mining Software in Java, http://www.cs.waikato.ac.nz/ml/weka/
  6. 6.
    Goldman, S.E., Stone, K.L., Ancoli-Israel, S., Blackwell, T., Ewing, S.K., Boudreau, R., Cauley, J.A., Hall, M., Matthews, K.A., Newman, A.B.: Poor Sleep is Associated with Poorer Physical Performance and Greater Functional Limitations in Older Women. In: Sleep (2007)Google Scholar
  7. 7.
    Tinetti, M.E., Speechley, M., Ginter, S.F.: Risk Factors for Falls among Elderly Persons Living in the Community. The New England Journal of Medicine (1988)Google Scholar
  8. 8.
  9. 9.
    Pollack, M.E.: Intelligent Technology for an Aging Population: The Use of AI to Assist Elders with Cognitive Impairment. AI Magazine (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yu Chun Yen
    • 1
  • Ching Hu Lu
    • 1
    • 2
  • Yi Chung Cheng
    • 1
  • Jing Siang Chen
    • 1
  • Li Chen Fu
    • 1
    • 3
  1. 1.Department of Computer ScienceNational Taiwan UniversityTaiwan
  2. 2.INSIGHT CenterNational Taiwan UniversityTaiwan
  3. 3.Department of Electrical EngineeringNational Taiwan UniversityTaipeiTaiwan

Personalised recommendations