Fall Detection on Embedded Platform Using Kinect and Wireless Accelerometer

  • Michal Kepski
  • Bogdan Kwolek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7383)

Abstract

In this paper we demonstrate how to accomplish reliable fall detection on a low-cost embedded platform. The detection is achieved by a fuzzy inference system using Kinect and a wearable motion-sensing device that consists of accelerometer and gyroscope. The foreground objects are detected using depth images obtained by Kinect, which is able to extract such images in a room that is dark to our eyes. The system has been implemented on the PandaBoard ES and runs in real-time. It permits unobtrusive fall detection as well as preserves privacy of the user. The experimental results indicate high effectiveness of fall detection.

Keywords

Fuzzy Inference System Depth Image Assistive Technology Foreground Object Wearable Device 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Anderson, D., Keller, J., Skubic, M., Chen, X., He, Z.: Recognizing falls from silhouettes. In: Annual Int. Conf. of the Engineering in Medicine and Biology Society, pp. 6388–6391 (2006)Google Scholar
  2. 2.
    Bourke, A., O’Brien, J., Lyons, G.: Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait & Posture 26(2), 194–199 (2007)CrossRefGoogle Scholar
  3. 3.
    Cook, A., Hussey, S.: Assistive Technologies — Principles and Practice, Mosby, 2nd edn. (2002)Google Scholar
  4. 4.
    Cucchiara, R., Prati, A., Vezzani, R.: A multi-camera vision system for fall detection and alarm generation. Expert Systems 24(5), 334–345 (2007)CrossRefGoogle Scholar
  5. 5.
    Degen, T., Jaeckel, H., Rufer, M., Wyss, S.: Speedy: A fall detector in a wrist watch. In: Proc. of IEEE Int. Symp. on Wearable Computers, pp. 184–187 (2003)Google Scholar
  6. 6.
    Heinrich, S., Rapp, K., Rissmann, U., Becker, C., König, H.H.: Cost of falls in old age: a systematic review. Osteoporosis International 21, 891–902 (2010)CrossRefGoogle Scholar
  7. 7.
    Kangas, M., Konttila, A., Lindgren, P., Winblad, I., Jamsa, T.: Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait & Posture 28(2), 285–291 (2008)CrossRefGoogle Scholar
  8. 8.
    Kepski, M., Kwolek, B., Austvoll, I.: Fuzzy Inference-Based Reliable Fall Detection Using Kinect and Accelerometer. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS, vol. 7267, pp. 266–273. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  9. 9.
    Miaou, S.-G., Sung, P.-H., Huang, C.-Y.: A customized human fall detection system using omni-camera images and personal information. In: Distributed Diagnosis and Home Healthcare, pp. 39–42 (2006)Google Scholar
  10. 10.
    Noury, N., Fleury, A., Rumeau, P., Bourke, A., Laighin, G., Rialle, V., Lundy, J.: Fall detection - principles and methods. In: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pp. 1663–1666 (2007)Google Scholar
  11. 11.
    Rougier, C., Meunier, J., St-Arnaud, A., Rousseau, J.: Monocular 3D head tracking to detect falls of elderly people. In: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pp. 6384–6387 (2006)Google Scholar
  12. 12.
    Takagi, T., Sugeno, M.: Fuzzy Identification of Systems and its Applications to Modeling and Control. IEEE Trans. on SMC 15(1), 116–132 (1985)MATHGoogle Scholar
  13. 13.
    Yu, X.: Approaches and principles of fall detection for elderly and patient. In: 10th Int. Conf. on e-health Networking, Applications and Services, pp. 42–47 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Michal Kepski
    • 1
  • Bogdan Kwolek
    • 1
  1. 1.Rzeszów University of TechnologyRzeszówPoland

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