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WiFall: Device-Free Fall Detection by Wireless Networks
- Source :
- IEEE Transactions on Mobile Computing. 16:581-594
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- Injuries that are caused by falls have been regarded as one of the major health threats to the independent living for the elderly. Conventional fall detection systems have various limitations. In this work, we first look for the correlations between different radio signal variations and activities by analyzing radio propagation model. Based on our observation, we propose WiFall, a truly unobtrusive fall detection system. WiFall employs physical layer Channel State Information (CSI) as the indicator of activities. It can detect fall of the human without hardware modification, extra environmental setup, or any wearable device. We implement WiFall on desktops equipped with commodity 802.11n NIC, and evaluate the performance in three typical indoor scenarios with several layouts of transmitter-receiver (Tx-Rx) links. In our area of interest, WiFall can achieve fall detection for a single person with high accuracy. As demonstrated by the experimental results, WiFall yields 90 percent detection precision with a false alarm rate of 15 percent on average using a one-class SVM classifier in all testing scenarios. It can also achieve average 94 percent fall detection precisions with 13 percent false alarm using Random Forest algorithm.
- Subjects :
- Computer Networks and Communications
Computer science
Wireless network
business.industry
010401 analytical chemistry
Real-time computing
020206 networking & telecommunications
Motion detection
02 engineering and technology
01 natural sciences
0104 chemical sciences
Constant false alarm rate
0202 electrical engineering, electronic engineering, information engineering
False alarm
Electrical and Electronic Engineering
business
Wireless sensor network
Software
Computer network
Subjects
Details
- ISSN :
- 15361233
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Mobile Computing
- Accession number :
- edsair.doi...........ed56653ed91c8eb3f8b1499d0931c00d