WmFall: WiFi-based multistage fall detection with channel state information
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...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-10-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718805718 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832553291456708608 |
|---|---|
| author | Xu Yang Fangyuan Xiong Yuan Shao Qiang Niu |
| author_facet | Xu Yang Fangyuan Xiong Yuan Shao Qiang Niu |
| author_sort | Xu Yang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c5f3088f91224979b5eb785d73108e2c |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-c5f3088f91224979b5eb785d73108e2c2025-02-03T05:54:31ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-10-011410.1177/1550147718805718WmFall: WiFi-based multistage fall detection with channel state informationXu YangFangyuan XiongYuan ShaoQiang NiuTraditional 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.https://doi.org/10.1177/1550147718805718 |
| spellingShingle | Xu Yang Fangyuan Xiong Yuan Shao Qiang Niu WmFall: WiFi-based multistage fall detection with channel state information International Journal of Distributed Sensor Networks |
| title | WmFall: WiFi-based multistage fall detection with channel state information |
| title_full | WmFall: WiFi-based multistage fall detection with channel state information |
| title_fullStr | WmFall: WiFi-based multistage fall detection with channel state information |
| title_full_unstemmed | WmFall: WiFi-based multistage fall detection with channel state information |
| title_short | WmFall: WiFi-based multistage fall detection with channel state information |
| title_sort | wmfall wifi based multistage fall detection with channel state information |
| url | https://doi.org/10.1177/1550147718805718 |
| work_keys_str_mv | AT xuyang wmfallwifibasedmultistagefalldetectionwithchannelstateinformation AT fangyuanxiong wmfallwifibasedmultistagefalldetectionwithchannelstateinformation AT yuanshao wmfallwifibasedmultistagefalldetectionwithchannelstateinformation AT qiangniu wmfallwifibasedmultistagefalldetectionwithchannelstateinformation |