DocumentCode
1797198
Title
Radar-based fall detection exploiting time-frequency features
Author
Ramirez Rivera, Luis ; Ulmer, Eric ; Zhang, Yimin D. ; Wenbing Tao ; Amin, Moeness G.
Author_Institution
Dept. of Electr. & Comput. Eng., Villanova Univ., Villanova, PA, USA
fYear
2014
fDate
9-13 July 2014
Firstpage
713
Lastpage
717
Abstract
Falls of the elderly are a major public health concern. In this paper, we develop an effective fall detection algorithm for application in continuous-wave radar systems. The proposed algorithm exploits time-frequency characteristics of the radar Doppler signatures, and the motion events are classified using the joint statistics of three different features. The effectiveness of the proposed technique is verified through measurement data.
Keywords
CW radar; Doppler radar; continuous wave radar systems; data measurement; joint statistics; motion events; public health; radar Doppler signatures; radar based fall detection; time frequency characteristics; time frequency features; Doppler effect; Doppler radar; Feature extraction; Radar detection; Spectrogram; Time-frequency analysis; Assisted living; classification; fall detection; time-frequency analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
Conference_Location
Xi´an
Print_ISBN
978-1-4799-5401-8
Type
conf
DOI
10.1109/ChinaSIP.2014.6889337
Filename
6889337
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