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Fall Detection for the Elderly by Accelerometers


Authors: H. Qian and X. Fan
Title: Fall Detection for the Elderly by Accelerometers
Abstract: Fall detection for the elderly is an ongoing active research topic because of the demanding needs of caring for the elderly. Falls are one of the most vital problems of the elderly. In the meantime, wearable sensors are light-weighted and convenient, and thus can be embedded into clothing, making it possible to promptly detect the falling situation in the daily life. Quick fall detection thus provides necessary help to avoid further harms. This paper gives an overview of the procedures of fall detection, as well as addressing issues in fall detection from wireless accelerometers. Experiments have been conducted on a publicly available data set for fall detection. SVM classifiers and kNN classifiers are implemented in different settings, with extensive analysis.
Keywords: Fall detection; Classification; Accelerometers
Journal Name: International Journal of Information Technology, vol. 23, no. 2
Publisher: Singapore Computer Society
Year: 2017
Accepted PDF File: Fall_Detection_for_the_Elderly_by_Accelerometers_accepted.pdf
Permanent Link: http://www.intjit.org/journal/download/down.php?file=/23/2/232_2.pdf
Reference: H. Qian and X. Fan, “Fall detection for the elderly by accelerometers,” International Journal of Information Technology, vol. 23, no. 2, pp. 1–12, 2017.
bibtex: 
@article{LILY-j42,
   author	= {Qian, Hangwei and Fan, Xiuyi}, 
   title	= {Fall Detection for the Elderly by Accelerometers}, 
   journal	= {International Journal of Information Technology}, 
   year		= {2017},  
   volume	= {23}, 
   number	= {2}, 
   pages	= {1-12},
   publisher 	= {Singapore Computer Society}, 
}