An Effective Noise Resistant FM Continuous-Wave Radar Vital Sign Signal Detection Method

To address the problem that the FM continuous-wave (FMCW) radar extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a backpropagation (BP) neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise, accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal to-noise ratio of the sign signals.

• Lu Yang
• Meiyang Song
• Xiang Yu
• Wenhao Zhou
• Chuntao Feng

• Frequency modulated continuous wave radar
• ICEEMDAN
• BP Neural Network
• vital signs signal.

[1] Celler B G, Sparks R S. Home telemonitoring of vital signs—technical
challenges and future directions (J). IEEE journal of biomedical and
health informatics, 2014, 19(1): 82-91.
[2] Xie L, Tian J, Li H, et al. Wireless Healthcare System for Life Detection
and Vital Sign Monitoring (C)//2020 IEEE 91st Vehicular Technology
Conference (VTC2020-Spring). IEEE, 2020: 1-5.
[3] Zheng Hongmei, Ge Miao, Chen Ke, et al. Separation study of heartbeat
signal and respiration signal based on FCEEMD (J). Journal of Electronic
Measurement and Instrumentation, 2017, 31(11): 1809-1814.
[4] Yen H T, Kurosawa M, Kirimoto T, et al. Proof-of-principle Experiment
on 24 GHz Medical Radar for Non-contact Vital Signs Measurement
(C)//2021 43rd Annual International Conference of the IEEE Engineering
in Medicine & Biology Society (EMBC). IEEE, 2021: 6884-6884.
[5] Chen W, Lan S, Zhang G. Multiple-Target Vital Signs Sensing using
77GHz FMCW radar (C)//2021 15th European Conference on Antennas
and Propagation (EU CAP). IEEE, 2021: 1-3.
[6] Shen H, Xu C, Yang Y, et al. Respiration and heartbeat rates measurement
based on autocorrelation using IR-UWB radar (J). IEEE transactions on
circuits and systems II: express briefs, 2018, 65(10): 1470-1474.
[7] Zakrzewski M, Raittinen H, Vanhala J. Comparison of center estimation
algorithms for heart and respiration monitoring with microwave Doppler
radar (J). IEEE Sensors Journal, 2011, 12(3): 627-634.
[8] Fang G W, Huang C Y, Yang C L. Switch-based low intermediate
frequency system of a vital sign radar for simultaneous multitarget and
multidirectional detection (J). IEEE Journal of Electromagnetics, RF and
Microwaves in Medicine and Biology, 2020, 4(4): 265-272.
[9] Sacco G, Piuzzi E, Pittella E, et al. Vital Signs Monitoring for Different
Chest Orientations Using an FMCW Radar (C)//2020 XXXIIIrd General
Assembly and Scientific Symposium of the International Union of Radio
Science. IEEE, 2020: 1-4.
[10] Pal S. FMCW–Radar Design: by M. Jankiraman, London, ARTECH
HOUSE, 2018, 415 pp., $179 (hardback), ISBN-13: 978-1-63081-567-7
(J). 2019.
[11] Cui LH, Zhao AX, Ning FZ. Radar sign signal detection algorithm based
on EMD and BP neural network[J]. Computer System Applications, 2017,
26(8): 217-222.
[12] Xiao Jialin, Yue Dianwu, Zhao Zhengduo, et al. Genetic algorithm-based
optimization of BP neural network for visible light localization (J).
Optoelectronics - Laser, 2019, 30(8): 810-816.