İnsan hareketleri̇ni̇n vi̇brasyon ve PIR algilayicilari kullanilarak siniflandirilmasi

Translated title of the contribution: Human activity classification using vibration and PIR sensors

Ahmet Yazar*, A. Enis Çetin, B. Uǧur Töreyin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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.

Translated title of the contributionHuman activity classification using vibration and PIR sensors
Original languageTurkish
Title of host publication2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 20th Signal Processing and Communications Applications Conference, SIU 2012 - Fethiye, Mugla, Turkey
Duration: 18 Apr 201220 Apr 2012

Publication series

Name2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings

Conference

Conference2012 20th Signal Processing and Communications Applications Conference, SIU 2012
Country/TerritoryTurkey
CityFethiye, Mugla
Period18/04/1220/04/12

Fingerprint

Dive into the research topics of 'Human activity classification using vibration and PIR sensors'. Together they form a unique fingerprint.

Cite this