Sleep Apnea Monitoring System Based on Commodity WiFi Devices  

作　　者：Xiaolong Yang Xin Yu Liangbo Xie Hao Xue Mu Zhou Qing Jiang 

机构地区：[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

出　　处：《Computers, Materials & Continua》2021年第11期2793-2806,共14页计算机、材料和连续体（英文）

基　　金：This work was supported by the National Natural Science Foundation of China(61771083,61704015);Science and Technology Research Project of Chongqing Education Commission(KJQN201800625);Chongqing Natural Science Foundation Project(cstc2019jcyjmsxmX0635).

摘　　要：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.

关 键 词：WIFI channel state information APNEA neural network 

分 类 号：TN9[电子电信—信息与通信工程]