DocumentCode :
2242893
Title :
Accelerometer-based fall detection sensor system for the elderly
Author :
Yanjun Li ; Gan Chen ; Yueyun Shen ; Yihua Zhu ; Zhen Cheng
Author_Institution :
Sch. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
1216
Lastpage :
1220
Abstract :
The considerable risk of falls and the substantial increase in the elderly population make the automatic fall detection system become very important. Existing fall detection systems using accelerometer as the detector are often designed based on an empirical acceleration threshold to differentiate falls from normal activities. In this paper, we design the detection method under the Neyman-Pearson detection framework. An optimal detection threshold can be obtained which meets the specified false alarm rate while maximizing the detection probability. We use TelosW mote with accelerometer as the detector, which is attached to the waist of the old people to capture the movement data. Extensive experiments are conducted to evaluate the effectiveness of our method and the accuracy of the detection system.
Keywords :
accelerometers; alarm systems; geriatrics; health care; sensors; wireless sensor networks; Neyman-Pearson detection framework; TelosW mote; accelerometer based fall detection sensor system; automatic fall detection system; detection probability; elderly population; empirical acceleration threshold; false alarm rate; optimal detection threshold; Acceleration; Accelerometers; Senior citizens; Sensor systems; Testing; Training; Training data; Neyman-Pearson model; accelerometer; fall detection; sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664577
Filename :
6664577
Link To Document :
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