TY - GEN
T1 - Simultaneous Detection of Multi-Target Vital Signs Using EEMD Algorithm Based on FMCW Radar
AU - Fang, Guan Wei
AU - Huang, Ching Yao
AU - Yang, Chin Lung
PY - 2019/5
Y1 - 2019/5
N2 - This paper presents a novel approach to simultaneously monitor multi-target vital-signs using a frequency modulation continuous wave (FMCW) radar within the resolution limitation. For a traditional system architecture on multi-target vital-signs monitoring, complicated systems are required such as phased array radar or continuous wave (CW) radar with beamforming technology. In contrast, this architecture has the advantage of enhanced resolution capability, relatively simple circuit, and low cost. By using advanced signal processing such as adaptive boundary, we can detect multi-target vital signs even though the difference of the distances to the two targets is less than the range resolution of FMCW radar. In terms of demodulation, heart rate (HR) is susceptible to the harmonic of respiratory rate (RR) using complex signal demodulation (CSD). Therefore, this paper uses an ensemble empirical mode decomposition (EEMD) algorithm to extract the intrinsic mode functions of RR and HR. Experiments show that, we can improve signal-to-noise ratio (SNR) and accuracy significantly using this algorithm. And the vital sign errors of the two targets separated at 70 cm and 50 cm are averagely 2.35% and 4.44%, respectively.
AB - This paper presents a novel approach to simultaneously monitor multi-target vital-signs using a frequency modulation continuous wave (FMCW) radar within the resolution limitation. For a traditional system architecture on multi-target vital-signs monitoring, complicated systems are required such as phased array radar or continuous wave (CW) radar with beamforming technology. In contrast, this architecture has the advantage of enhanced resolution capability, relatively simple circuit, and low cost. By using advanced signal processing such as adaptive boundary, we can detect multi-target vital signs even though the difference of the distances to the two targets is less than the range resolution of FMCW radar. In terms of demodulation, heart rate (HR) is susceptible to the harmonic of respiratory rate (RR) using complex signal demodulation (CSD). Therefore, this paper uses an ensemble empirical mode decomposition (EEMD) algorithm to extract the intrinsic mode functions of RR and HR. Experiments show that, we can improve signal-to-noise ratio (SNR) and accuracy significantly using this algorithm. And the vital sign errors of the two targets separated at 70 cm and 50 cm are averagely 2.35% and 4.44%, respectively.
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U2 - 10.1109/IMBIOC.2019.8777810
DO - 10.1109/IMBIOC.2019.8777810
M3 - Conference contribution
T3 - IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings
BT - IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019
Y2 - 6 May 2019 through 8 May 2019
ER -
