Fuzzy Inference-Based Reliable Fall Detection Using Kinect and Accelerometer

  • Michal Kepski
  • Bogdan Kwolek
  • Ivar Austvoll
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7267)

Abstract

Falls are major causes of mortality and morbidity in the elderly. However, prevalent methods only utilize accelerometers or both accelerometers and gyroscopes to separate falls from activities of daily living. This makes it not easy to distinguish real falls from fall-like activities. The existing CCD-camera based solutions require time for installation, camera calibration and are not generally cheap. In this paper we show how to achieve reliable fall detection. The detection is done by a fuzzy inference system using low-cost Kinect and a device consisting of an accelerometer and a gyroscope. The experimental results indicate high accuracy of the detection and effectiveness of the system.

Keywords

Membership Function Fuzzy Inference System Depth Image Fall Detection Fuzzy Inference Engine 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Michal Kepski
    • 1
  • Bogdan Kwolek
    • 1
  • Ivar Austvoll
    • 2
  1. 1.Rzeszów University of TechnologyRzeszówPoland
  2. 2.University of StavangerStavangerNorway

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