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
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;
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
DOI :
10.1109/ChinaSIP.2014.6889337
