Human activity classification using vibration and PIR sensors [İnsan hareketleri̇ni̇n vi̇brasyon ve PIR algilayicilari kullanilarak siniflandirilmasi]
2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28188
Fall detection is an important problem for elderly people living independently and people in need of care. In this paper, a fall detection method using seismic and passive infrared (PIR) sensors is proposed. Fast Fourier transform, mel-frequency cepstrum coefficients, and discrete wavelet transform based features are extracted for classification. Seismic signals are classified into "fall" and "not a fall" classes using support vector machines. Once a moving person is detected by the PIR sensor within a region of interest, fall is detected by fusing seismic and PIR sensor decisions. The proposed system is implemented on a standard personal computer and works in real-time. © 2012 IEEE.
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