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Falling Person Detection Using Multi-Sensor Signal Processing

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.

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Correspondence to B. Ugur Toreyin.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Toreyin, B.U., Soyer, A.B., Onaran, I. et al. Falling Person Detection Using Multi-Sensor Signal Processing. EURASIP J. Adv. Signal Process. 2008, 149304 (2007). https://doi.org/10.1155/2008/149304

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Keywords

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