Research and Design of Radar System for Respiratory and Heartbeat Signal Detection

Authors

  • ziliang xia National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China
  • Xinhuai Wang National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China
  • Xin Li National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China
  • Yin Xu National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China

DOI:

https://doi.org/10.13052/2022.ACES.J.370112

Keywords:

Non-contact, Radar, Respiratory and heartbeat signals detection

Abstract

The respiratory and heartbeat signals can accurately reflect the health status of the tester, which is of great clinical significance. Compared with the traditional contact detection method, the non-contact radar detection method does not require the tester to wear any sensor equipment and will not cause any discomfort to the tester. The frequency modulated continuous wave (FMCW) radar has the characteristics of simple structure, high resolution, strong stability, and low transmission power and is used for the detection of respiratory and heartbeat signals. This paper designs a low-power, low-cost respiratory, and heartbeat signal detection system based on FMCW radar. In addition, the variational modal decomposition (VMD) method is used to separate respiration and heartbeat signals to obtain accurate respiration and heartbeat rates. The results show that the radar system for detecting respiratory and heartbeat signals has high detection accuracy.

Downloads

Download data is not yet available.

Author Biographies

ziliang xia, National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China

Ziliang Xia received the B.S. degree from the Xidian University, Xi’an, China, in 2019. He is currently working toward the M.S. degree in electromagnetic field and microwave technology with the same university. His recent research interests are mainly in the design of circuits and algorithms.

Xinhuai Wang, National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China

Xinhuai Wang received the B.Eng., M.Eng., and Ph.D. degrees from Xidian University, Xi’an, China, in 2004, 2007, and 2011, respectively. Since 2011, he has been with Collaborative Innovation Center of Information Sensing and Understanding, Xidian University and Science and Technology on Antenna and Microwave Laboratory, Xidian University, as a Lecturer and Associate Professor. He has authored or coauthored more than 60 international and regional refereed journal papers. His recent research interests are mainly in the design of microwave components system.

Dr. Wang is a member of IEEE and a senior member of CIE.

Xin Li, National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China

Xin Li was born in 1995. He received the B.S. degree from the Xidian University, Xi’an, China, in 2019. He is currently working toward the M.S. degree in electromagnetic field and microwave technology with the same university. His recent research interests are mainly in the signal processing and the design ofcircuits.

Yin Xu, National Key Laboratory of Science and Technology on Antennas and Microwave Xidian University, Xi’an, Shaanxi 710071, China

Yin Xu received the B.Eng., M.Eng., and Ph.D. degrees from Xidian University, Xi’an, China, in 2006, 2009, and 2013, respectively.

She is working at Xidian University as an associate professor. Her recent research interests are mainly in the electromagnetic field and microwave technology.

References

The Writing Committee of the Report on Cardiovascular Health and Diseases in China, “Report on cardiovascular health and diseases burden in china: an updated summary of 2020,” Chinese Circulation Journal., vol. 36, pp. 521–545, Jun. 2021.

Y. H. Kwak, et al., “Flexible heartbeat sensor for wearable device,” Biosensors & Bioelectronics., vol. 94, pp. 250–255, Mar 2017.

F. Q. Qi, et al., “Detection and classification of finer-Grained human activities based on stepped-frequency continuous-wave through-wall radar,” Sensors., vol. 16, no. 6, pp. 885–901, Jun. 2016.

A. D. Droitcour, et al., “Range correlation and I/Q performance benefits in single-chip silicon Doppler radars for noncontact cardiopulmonary monitoring,” IEEE Transactions on Microwave Theory & Techniques., vol. 52, no. 3, pp. 838–848, Mar. 2004.

M. Brink, C. H. Müller, and C. Schierz, “Contact-free measurement of heart rate, respiration rate, and body movements during sleep,” Behavior Research Methods., vol.38, no. 3, pp. 511–521, Aug. 2006.

M. Uenoyama, T. Matsui, K. Yamada, et al., “Non-contact respiratory monitoring system using a ceiling-attached microwave antenna,” Medical & Biological Engineering & Computing., vol. 44, no. 9, pp. 835–840, 2006.

Y. Xu, J. Chen, S. Dai, et al., “Experimental study of UWB pulse radar for life detection,” Instrumentation, Measurement, Computer, Communication and Control., 2011 pp. 729–732.

L. Anitori, A. D. Jong, F. Nennie, “FMCW radar for life-sign detection,” IEEE Radar Conference., 2009. pp. 1–6.

D. Zhang, M. Kurata, T. Inaba, “FMCW radar for small displacement detection of vital signal using projection matrix method,” International Journal of Antennas and Propagation., 2013, pp. 1–5.

R. S. Mpanda, et al. “Design and evaluation of typical antennas for monitoring vital signs,” Applied Computational Electromagnetics Society journal., vol. 34, no. 3, pp. 497-505, Mar. 2019.

D. R. Morgan, M. G. Zierdt, “Novel signal processing techniques for Doppler radar cardiopulmonary sensing,” Signal Processing., vol. 89, no. 1,pp. 45–66, 2009.

M. Y. Li, J. Lin, “Wavelet-transform-based data-length-variation technique for fast heart rate detection using 5.8-ghz CW Doppler radar,” IEEE Transactions on Microwave Theory and Techniques., vol.66, no. 1, pp. 568–576, 2018.

N. E. Huang, Z. Shen, S. R. Long, et al., “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences., vol. 454, no. 1971, pp. 903–995, 1998.

Z. Wu, N. E. Huang, X. Chen, “The multi-dimensional ensemble empirical mode decomposition method,” Advances in Adaptive DataAnalysis., vol. 1, no. 3, pp. 339–372, 2009.

Z. Wu, N. E. Huang, “Ensemble empirical mode decomposition: a noise-assisted data analysis method,” Advances in adaptive data analysis., vol.1, no. 1, pp. 1–41, 2009.

M. E. Torre, M. A. Colominas, et al., “A completeensemble empirical mode decomposition with adaptive noise,” IEEE International Conference on Acoustics, Speech and Signal Processing., 2011, pp. 4144–4147.

K. Dragomiretskiy, D. Zosso, “Variational mode decomposition,” IEEE Transactions on Signal Processing., vol.62, no. 3, pp. 531–544, 2014.

Downloads

Published

2022-01-31

How to Cite

[1]
ziliang xia, X. Wang, X. Li, and Y. Xu, “Research and Design of Radar System for Respiratory and Heartbeat Signal Detection”, ACES Journal, vol. 37, no. 1, pp. 102–108, Jan. 2022.

Issue

2022: Vol 37 Iss 1

Section

General Submission

Categories