Falling person detection using multi-sensor signal processing
Töreyin, Behçet Uğur
Soyer, Emin Birey
Çetin, Ahmet Enis
Proceedings of the 15th Signal Processing and Communications Applications, IEEE 2007
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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. In this paper, signals produced by sound and passive infrared (PIR) sensors are simultaneously analyzed to detect suddenly falling elderly people. A typical room in a supportive home can be equipped with sound and PIR sensors. Hidden Markov models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs can be fused together to reach a final decision.