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

Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

Abstract:

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.

Keywords: Frequency modulated continuous wave radar, ICEEMDAN, BP Neural Network, vital signs signal.

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References:


[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.