A fall detection algorithm based on channel state information

Human motion detection based on CSI (Channel State Information) is a hot research topic. Many researchers started to focus on it. In this paper, we employ the CSI to detect fall behavior. Firstly, a data weighting operation to smooth the noise will be implemented. Secondly, we extract behaviors data...

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Bibliographic Details
Published in2017 International Smart Cities Conference (ISC2) pp. 1 - 4
Main Authors Keming Tang, Yong Xu, Hao Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Channel state information
Classification algorithms
CSI
Data mining
fall detection
Feature extraction
human motion
Neural networks
Wireless communication
Wireless fidelity
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DOI10.1109/ISC2.2017.8090862

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Summary:Human motion detection based on CSI (Channel State Information) is a hot research topic. Many researchers started to focus on it. In this paper, we employ the CSI to detect fall behavior. Firstly, a data weighting operation to smooth the noise will be implemented. Secondly, we extract behaviors data by effect size. Thirdly, several features will be extracted to represent the original data. Finally, we use neural network to distinguish fall behaviors between several behaviors. Experimental results show a better accuracy of our algorithm.
DOI:10.1109/ISC2.2017.8090862