Falling person detection using multisensor signal processing

B. Ugur Toreyin; E. Birey Soyer; Ibrahim Onaran; E. Enis Cetin

doi:10.1155/2008/149304

Falling person detection using multisensor signal processing

B. Ugur Toreyin^*, E. Birey Soyer, Ibrahim Onaran, E. Enis Cetin

^*Corresponding author for this work

Bilkent University

Research output: Contribution to journal › Article › peer-review

38 Citations (Scopus)

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.

Original language	English
Article number	149304
Journal	Eurasip Journal on Advances in Signal Processing
Volume	2008
DOIs	https://doi.org/10.1155/2008/149304
Publication status	Published - 2008
Externally published	Yes

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Falling person detection using multisensor signal processing

Abstract

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