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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Wi-Breath: Monitoring Sleep State with Wi-Fi Devices and Estimating Respiratory Rate
verfasst von : Xin Yu, Xiaolong Yang, Mu Zhou, Yong Wang
Erschienen in: Communications, Signal Processing, and Systems
Verlag: Springer Singapore
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Abstract
As one of the human health detection indicators, breath is becoming the research emphasis. Traditional approaches based on wearable devices or pressure sensor devices are expensive to manufacture, and not suitable for daily use. In this paper, we present Wi-Breath, a monitoring system that extract the disturbing parts from received signals and estimate respiratory rate of the rest. We use wavelet transform to remove the noise of the signal amplitude. Then, by analyzing the time–frequency information of the signal, we use the sliding window method to segment the signal. In addition, we use the Fourier transform (FT) to calculate the respiratory rate of the rest. Experimental results show that Wi-Breath can reliably remove the disturbing part of the signal and estimate the approximate respiratory frequency.