Skip to main content

Activity Recognition in Assisted Living Facilities with Incremental, Approximate Ground Truth

  • Conference paper
  • First Online:
Inclusive Smart Cities and e-Health (ICOST 2015)

Abstract

In this paper we present the problems associated with acquisition of ground truth, which is a critical step in facilitating accurate and automated care in Assisted Living Facilities. The approach permits both bottom up and top down methods of reasoning about data. The tradeoffs between granularity of ground truth acquisition and its impact on the detection rate are presented. It is suggested that the acquisition of ground truth should become a seamless operation incorporated transparently into the workflow of operations in these facilities. It is expected that with automation of collection, the increasing corpus of ground truth will lead to steady improvements in the detection rate and therefore the quality of automated monitoring and care provisioning. The methodology and models are substantiated with real data from two assisted living facilities, one in Singapore and the other in France. Although the results are preliminary they are quite promising.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Biswas, J., Mokhtari, M., Dong, J.S., Yap, P.: Mild Dementia Care at Home – Integrating Activity Monitoring, User Interface Plasticity and Scenario Verification. In: Lee, Y., Bien, Z.Z., Mokhtari, M., Kim, J.T., Park, M., Kim, J., Lee, H., Khalil, I. (eds.) ICOST 2010. LNCS, vol. 6159, pp. 160–170. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Mokhtari, M., Aloulou, H., Tiberghien, T., Biswas, J., Racoceanu, D., Yap, P.: New trends to support independence in persons with mild dementia - a mini-review. In: Gerontology, Karger (2012). doi:10.1159/000337827

  3. Biswas, et al.: Monitoring of Elderly in Assisted Living Facilities: a multi-sensor approach (submitted for publication)

    Google Scholar 

  4. Rabiner, L.: A tutorial on hidden Markov models and selected applications in speech recognition. In: Proceedings of the IEEE, vol. 77, no. 2, pp. 257–286. IEEE

    Google Scholar 

  5. Murphy, K.: Dynamic Bayesian Networks: Representation, Inference and Learning, Ph.D thesis, the University of California at Berkeley (2002)

    Google Scholar 

  6. Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering 22(10), October 2010. IEEE

    Google Scholar 

  7. Dong, G., Li, J.: Efficient mining of emerging patterns: discovering trends and differences. In: Proceedings of the Conference on Knowledge Discovery and Data Mining (KDD), pp. 43–52. ACM (1999)

    Google Scholar 

  8. Tolstikov, A., Hong, X., Biswas, J., Nugent, C., Chen, L., Parente, G.: Comparison of Fusion Methods Based on DST and DBN in Human Activity Recognition. Journal of Control Theory and Applications 9(1), 18–27 (2011). Springer Verlag

    Article  Google Scholar 

  9. http://www.careinnovations.com (last accessed February 26, 2015)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Romain Endelin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Biswas, J. et al. (2015). Activity Recognition in Assisted Living Facilities with Incremental, Approximate Ground Truth. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19312-0_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19311-3

  • Online ISBN: 978-3-319-19312-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics