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  • Research Article
  • Open Access

Falling Person Detection Using Multi-Sensor Signal Processing

  • 1Email author,
  • 1,
  • 1 and
  • 1
EURASIP Journal on Advances in Signal Processing20072008:149304

https://doi.org/10.1155/2008/149304

  • Received: 28 February 2007
  • Accepted: 12 September 2007
  • Published:

Abstract

Falls are one of the most important problems for frail and elderly people living independently. Early detection of falls is vital to provide a safe and active lifestyle for elderly. Sound, passive infrared (PIR) and vibration sensors can be placed in a supportive home environment to provide information about daily activities of an elderly person. In this paper, signals produced by sound, PIR and vibration sensors are simultaneously analyzed to detect falls. Hidden Markov Models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs are fused together to reach a final decision.

Keywords

  • Information Technology
  • Signal Processing
  • Daily Activity
  • Markov Model
  • Elderly People

Publisher note

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Authors’ Affiliations

(1)
Department of Electrical and Electronics Engineering, Bilkent University, Bilkent, Ankara, 06800, Turkey

Copyright

© B. Ugur Toreyin et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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