A fall detection algorithm based on channel state information

2017 ◽  
Author(s):  
Keming Tang ◽  
Yong Xu ◽  
Hao Yang
Keyword(s):  
Channel State Information ◽  
Fall Detection ◽  
Detection Algorithm ◽  
Channel State ◽  
State Information

scholarly journals WmFall: WiFi-based multistage fall detection with channel state information

2018 ◽  
Vol 14 (10) ◽  
pp. 155014771880571 ◽  
Author(s):  
Xu Yang ◽  
Fangyuan Xiong ◽  
Yuan Shao ◽  
Qiang Niu
Keyword(s):  
Channel State Information ◽  
Learning Algorithm ◽  
Detection System ◽  
Fall Detection ◽  
Special Method ◽  
Special Equipment ◽  
Channel State ◽  
State Information ◽  
Detection Systems ◽  
Deep Learning Algorithm

Traditional fall detection systems require to wear special equipment like sensors or cameras, which often brings the issues of inconvenience and privacy. In this article, we introduce a novel multistage fall detection system using the channel state information from WiFi devices. Our work is inspired by the fact that different actions have different effects on WiFi signals. By fully analyzing and exploring the channel state information characters, the falling actions can be distinguished from other movements. Considering that falling and sitting are very similar to each other, a special method is designed for distinguishing them with deep learning algorithm. Finally, the fall detection system is evaluated in a laboratory, which has 89% detection precision with false alarm rate of 8% on the average.

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