A method for automatic fall detection of elderly people using floor vibrations and soundProof of concept on human mimicking doll falls

Yaniv Zigel, Dima Litvak, Israel Gannot

Research output: Contribution to journalArticle

Abstract

Falls are a major risk for the elderly people living independently. Rapid detection of fall events can reduce the rate of mortality and raise the chances to survive the event and return to independent living. In the last two decades, several technological solutions for detection of falls were published, but most of them suffer from critical limitations. In this paper, we present a proof of concept to an automatic fall detection system for elderly people. The system is based on floor vibration and sound sensing, and uses signal processing and pattern recognition algorithm to discriminate between fall events and other events. The classification is based on special features like shock response spectrum and mel frequency ceptral coefficients. For the simulation of human falls, we have used a human mimicking doll: Rescue Randy. The proposed solution is unique, reliable, and does not require the person to wear anything. It is designed to detect fall events in critical cases in which the person is unconscious or in a stress condition. From the preliminary research, the proposed system can detect human mimicking dolls falls with a sensitivity of 97.5 and specificity of 98.6.

Original languageEnglish (US)
Article number5223652
Pages (from-to)2858-2867
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume56
Issue number12
DOIs
StatePublished - Dec 1 2009
Externally publishedYes

Keywords

  • Acoustic signal processing
  • Fall detector
  • Feature extraction
  • Pattern recognition
  • Transducers

ASJC Scopus subject areas

  • Biomedical Engineering

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