Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/1912
Title: RF-Based Noncontact Respiratory Rate Monitoring With Parametric Spectral Estimation
Authors: Uysal, Can
Filik, Tansu
Keywords: Monitoring
Estimation
Sensors
Receivers
Signal resolution
Doppler radar
Radio transmitters
Noncontact
ESPRIT
healthcare
respiratory rate
remote sensing
Issue Date: 2019
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Abstract: Respiratory rate (RR) monitoring of an adult or an infant during sleep or in steady position can be lifesaving, especially in home care systems. In this paper, we examine the potentials of wireless radio frequency (RF) signals to monitor the RR. A new noncontact RR monitoring system is proposed. The system includes a simple motion detection algorithm based on adaptive thresholding to eliminate the effects of the large-scale body movements on the RR estimation. In the proposed system, the high resolution subspace-based parametric spectral estimation approaches, estimation of signal parameters by rotational invariance technique (ESPRIT) and multiple signal classification (MUSIC), are presented as the RR estimation algorithms. According to our knowledge, the ESPRIT algorithm, which estimates the spectrum without searching, is used for the first time in this paper for RR estimation. It is shown that ESPRIT is computationally efficient and works approximately 49 times faster than the MUSIC algorithm. It is also shown with various experiments conducted with ten volunteers that the proposed noncontact RR monitoring system attains 0.13 breath per minute (bpm) error rate with the limited number of data and outperforms the periodogram method commonly used as the benchmark.
URI: https://doi.org/10.1109/JSEN.2019.2927536
https://hdl.handle.net/20.500.13087/1912
ISSN: 1530-437X
1558-1748
Appears in Collections:Elektrik-Elektronik Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

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