EURASIP Journal on Advances in Signal Processing 
Volume 2008 (2008), Article ID 149304, 7 pages
doi:10.1155/2008/149304
Research Article

Falling Person Detection Using Multi-Sensor Signal Processing

B. Ugur Toreyin, E. Birey Soyer, Ibrahim Onaran, and A. Enis Cetin

 Department of Electrical and Electronics Engineering, Bilkent University, Bilkent 06800, Ankara, Turkey
Received 28 February 2007; Accepted 12 September 2007

Recommended by Eric Pauwels

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.