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, Fethiye, Mugla, Turkey, 18 - 20 April 2012, (Full Text)
- Publication Type: Conference Paper / Full Text
- Doi Number: 10.1109/siu.2012.6204718
- City: Fethiye, Mugla
- Country: Turkey
- Open Archive Collection: AVESIS Open Access Collection
- Eskisehir Osmangazi University Affiliated: Yes
Abstract
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.