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Open AccessArticle

R-DEHM: CSI-Based Robust Duration Estimation of Human Motion with WiFi

1
School of Information & Electrical Engineering, Hebei University of Engineering, Handan 056038, Hebei, China
2
Hebei Key Laboratory of Security & Protection Information Sensing and Processing, Handan 056038, Hebei, China
3
Department of Public Sports, Hebei University of Engineering, Handan 056038, Hebei, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(6), 1421; https://doi.org/10.3390/s19061421
Received: 27 February 2019 / Revised: 13 March 2019 / Accepted: 15 March 2019 / Published: 22 March 2019
(This article belongs to the Section Sensor Networks)
As wireless sensing has developed, wireless behavior recognition has become a promising research area, in which human motion duration is one of the basic and significant parameters to measure human behavior. At present, however, there is no consideration of the duration estimation of human motion leveraging wireless signals. In this paper, we propose a novel system for robust duration estimation of human motion (R-DEHM) with WiFi in the area of interest. To achieve this, we first collect channel statement information (CSI) measurements on commodity WiFi devices and extract robust features from the CSI amplitude. Then, the back propagation neural network (BPNN) algorithm is introduced for detection by seeking a cutting line of the features for different states, i.e., moving human presence and absence. Instead of directly estimating the duration of human motion, we transform the complex and continuous duration estimation problem into a simple and discrete human motion detection by segmenting the CSI sequences. Furthermore, R-DEHM is implemented and evaluated in detail. The results of our experiments show that R-DEHM achieves the human motion detection and duration estimation with the average detection rate for human motion more than 94% and the average error rate for duration estimation less than 8%, respectively. View Full-Text
Keywords: duration estimation; human motion detection; channel statement information; back propagation neural network; WiFi duration estimation; human motion detection; channel statement information; back propagation neural network; WiFi
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MDPI and ACS Style

Zhao, J.; Liu, L.; Wei, Z.; Zhang, C.; Wang, W.; Fan, Y. R-DEHM: CSI-Based Robust Duration Estimation of Human Motion with WiFi. Sensors 2019, 19, 1421.

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