Falling Person Detection Using Multi-Sensor Signal Processing. (22nd November 2007)

• Record Type: Journal Article
• Authors: Toreyin Toreyin, B. Ugur B. Ugur; Soyer Soyer, E. Birey E. Birey; Onaran Onaran, Ibrahim Ibrahim; Cetin Cetin, A. Enis A. Enis
• Other Names: Pauwels Pauwels Eric Eric Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2007-11-22
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/149304
• Languages: English
• ISSNs: 1687-6172

Abstract

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.