Research Article
Sleep Apnea Monitoring System Based on Channel State Information
@INPROCEEDINGS{10.1007/978-3-030-77569-8_3, author={Xiaolong Yang and Xin Yu and Liangbo Xie and Mu Zhou and Qing Jiang}, title={Sleep Apnea Monitoring System Based on Channel State Information}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 16th EAI International Conference, QShine 2020, Virtual Event, November 29--30, 2020, Proceedings}, proceedings_a={QSHINE}, year={2021}, month={6}, keywords={WiFi Channel state information Sleep apnea}, doi={10.1007/978-3-030-77569-8_3} }- Xiaolong Yang
Xin Yu
Liangbo Xie
Mu Zhou
Qing Jiang
Year: 2021
Sleep Apnea Monitoring System Based on Channel State Information
QSHINE
Springer
DOI: 10.1007/978-3-030-77569-8_3
Abstract
Sleep apnea is an important factor that affects human health. Traditional approaches based on wearable devices or pressure sensor devices are too expensive to be suitable for daily use, which also don’t consider the impact on the breathing frequency when the human body turns over or gets up. In this paper, we propose a system based on WiFi to monitor sleep apnea state. Firstly, we use linear fitting to eliminate the phase errors of the receiving antennas, and wavelet transform to remove the noise of signal amplitude. Secondly, we combine the short-time Fourier transform and sliding window method to segment the signal. Finally, the features such as the variance of the phase difference between antennas are extracted, and the neural network model is built to identify apnea state, so as to eliminate interference caused by changes in sleep postures. Experiment results show that the detection accuracy rate for sleep apnea is over 95.6%. Our system can be a daily apnea monitoring approach and provide health reference for users.
