Open Access

ARTICLE

Sleep Apnea Monitoring System Based on Commodity WiFi Devices

Xiaolong Yang¹, Xin Yu¹, Liangbo Xie^1,*, Hao Xue², Mu Zhou¹, Qing Jiang¹

1 School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
2 School of Computing Technologies, RMIT University, Melbourne, Victoria, 3001, Australia

* Corresponding Author: Liangbo Xie. Email:

Computers, Materials & Continua 2021, 69(2), 2793-2806. https://doi.org/10.32604/cmc.2021.016298

Received 29 December 2020; Accepted 19 May 2021; Issue published 21 July 2021

Abstract

To address the limitations of traditional sleep monitoring methods that highly rely on sleeping posture without considering sleep apnea, an intelligent apnea monitoring system is designed based on commodity WiFi in this paper. By utilizing linear fitting and wavelet transform, the phase error of channel state information (CSI) of the receiving antenna is eliminated, and the noise of the signal amplitude is removed. Moreover, the short-time Fourier transform (STFT) and sliding window method are combined to segment received wireless signals. Finally, several important statistical characteristics are extracted, and a back propagation (BP) neural network model is built to identify apnea state. Thus, interferences caused by changes of sleeping posture are eliminated. Extensive experimental results demonstrate that the proposed system can identify apnea state with an accuracy of over 95.6%. Furthermore, the accuracy can still reach more than 94.8% when the test environment layout is changed. Therefore, the proposed system can be used as a daily apnea monitoring system at home and provide users with health information.

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Keywords

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