Advertisement

Unobtrusive Fall Detection Using 3D Images of a Gaming Console: Concept and First Results

  • Christian Marzahl
  • Peter Penndorf
  • Ilvio Bruder
  • Martin Staemmler
Part of the Advanced Technologies and Societal Change book series (ATSC)

Abstract

Image based fall detection is costly and rated obtrusive by those being monitored. The approach presented in this paper uses a cost efficient gaming console for 3D image generation. The image itself covers a range of about up to 30cm above the floor and allows for a nearly invisible positioning e.g. under the bed. Image analysis allows classifying events like “feet in front of the bed”, “fall”, “leaving the room” and “activity in the room”. For use in nursing homes and in home environments a system design has been implemented which is compatible with the guidelines of the Continua Health Alliance and fulfils data privacy requirements. The system supports the nursing home in its obligations for documentation of events. It was successfully tested in a laboratory environment and in a small scale test using three rooms of a nursing home in order to prepare for a large scale trial.

Keywords

Fall detection 3D image analysis fall prevention standards Personal Health AAL 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Center for Disease Control and Prevention, http://www.cdc.gov/HomeandRecreationalSafety/Falls/adultfalls.html (last visited August 29, 2011)
  2. 2.
    Tunstall: Sturzdetektion, http://www.hausnotruf-shop.de/Tunstall-Piper-FallDetector (last visited July 29, 2011)
  3. 3.
    Sen Cit +  monitors , http://www.sendtech.co.uk/SeN-Cit/reg_move.shtml (last visited August 29, 2011)
  4. 4.
    Wu, G., Xue, S.: Portable preimpact fall detector with inertial sensors. IEEE Trans. Neural Syst. Rehabil. Eng. 16(2), 178–183 (2008)CrossRefGoogle Scholar
  5. 5.
    Salomon, R., Lüder, M., Bieber, G.: Vorrichtung und Verfahren zur Sturzerkennung. Patentschrift, DE 102009019767 (2009)Google Scholar
  6. 6.
    signaKom: Sturzmatte, http://www.signakom.ch/kontaktmatte_sturzmatte.html (last visited August 29, 2011)
  7. 7.
    Future Shape: SensFloor Fußboden, http://www.future-shape.de/sensfloor.html (last visited August 29, 2011)
  8. 8.
    BMBF Projekt SensFloor, http://www.sensfloor.de (last visited August 29, 2011)
  9. 9.
    Gövercin, M., Spehr, J., Winkelbach, S., Steinhagen-Thiessen, E., Wahl, F.: Visual fall detection system in home environments. Gerontechnology 7(2), 114 (2008)Google Scholar
  10. 10.
    Projekt SENS@HOME, http://www.vitracom.de/de/f-a-e/senshome.html (last visited August 29, 2011)
  11. 11.
    Funktionsprinzip Kinect, triangulation, http://mirror2image.wordpress.com/2010/11/30/how-kinect-works-stereo-triangulation/ (last visited August 29, 2011)
  12. 12.
    Microsoft Kinect, http://www.xbox.com/de-DE/Xbox360/Accessories/kinect/Home (last visited August 29, 2011)
  13. 13.
    SDK beta Kinect for Windows, http://researchmicrosoft.com/en-us/um/redmond/projects/kinectsdk/about.aspx (last visited August 29, 2011)
  14. 14.
    Diraco, G., Leone, A., Siciliano, P.: An Active Vision System for Fall Detection and Posture Recognition in Elderly Healthcare. In: Proceedings of the Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 1536–1541 (2010)Google Scholar
  15. 15.
    Rougier, C., Auvinet, E., Rousseau, J., Mignotte, M., Meunier, J.: Fall Detection from Depth Map Video Sequences. In: Abdulrazak, B., Giroux, S., Bouchard, B., Pigot, H., Mokhtari, M. (eds.) ICOST 2011. LNCS, vol. 6719, pp. 121–128. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  16. 16.
    Velasco, F., Torres, J.C.: Cell Octree: A New Data Structure for Volume Modeling and Visualization. In: VI Fall Workshop on Vision, Modeling and Visualization, pp. 665–672 (2001)Google Scholar
  17. 17.
    Continua Health Alliance, http://www.continuaalliance.org/index.html (last visited August 29, 2011)
  18. 18.
    ubuntu, http://www.ubuntu.com (last visited August 29, 2011)
  19. 19.
    OpenNI, http://www.openni.org/ (last visited August 29, 2011)
  20. 20.
    Mono, http://www.mono-project.com/Main_Page (last visited August 29, 2011)
  21. 21.
    Asterisk, http://www.asterisk.org/ (last visited August 29, 2011)
  22. 22.

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Christian Marzahl
    • 1
  • Peter Penndorf
    • 1
  • Ilvio Bruder
    • 2
  • Martin Staemmler
    • 1
  1. 1.ETIUniversity of Applied SciencesStralsundGermany
  2. 2.Institute for Computer ScienceUniversity RostockRostockGermany

Personalised recommendations