Human activity classification using vibration and PIR sensors İnsan hareketleri̇ni̇n vi̇brasyon ve PIR algilayicilari kullanilarak siniflandirilmasi

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YAZAR A., Çetin A. E., Töreyin B. U.

2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Fethiye, Mugla, Türkiye, 18 - 20 Nisan 2012 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2012.6204718
  • Basıldığı Şehir: Fethiye, Mugla
  • Basıldığı Ülke: Türkiye
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

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.