Falling Person Detection Using Multi-Sensor Signal Processing

被引：0

作者：

B. Ugur Toreyin

A. Birey Soyer

Ibrahim Onaran

E. Enis Cetin

机构：

[1] Bilkent University,Department of Electrical and Electronics Engineering

来源：

EURASIP Journal on Advances in Signal Processing | / 2008卷

关键词：

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

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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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