文章基本信息

标题：WmFall: WiFi-based multistage fall detection with channel state information
本地全文：下载
作者：Xu Yang ; Fangyuan Xiong ; Yuan Shao 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2018
卷号：14
期号：10
页码：1
DOI：10.1177/1550147718805718
出版社：Hindawi Publishing Corporation
摘要：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.
关键词：Channel state information; fall detection; system; WiFi devices