ASVME

Citation Author(s):
zhen
yang
He Fei University of Technology
Submitted by:
zhen yang
Last updated:
Mon, 10/21/2024 - 05:51
DOI:
10.21227/hs58-pq35
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Abstract 

The breath rate (BR), heart rate (HR), breathing-breathing interval (BBI) and heart rate variability (HRV) are the critical vital sign parameters. In this article, a novel method named adaptive separation variational mode extraction algorithm (ASVME) is proposed to accurately monitor multi-variable vital signs (MVVS) at the same time with a frequency-modulated continuous wave (FMCW) radar system in practical scenarios. Firstly, a minimum variance distortionless response (MVDR) spectrum estimation algorithm is proposed to accurately locate respiratory and heartbeat components, which can effectively restrain the influence of respiratory harmonics on HR and R-R intervals (RRI) measurements. Subsequently, an adaptive variational mode extraction (AVME) algorithm is proposed to accurately extract respiratory waves and heartbeat waves after accurate frequency location. 

Instructions: 

The breath rate (BR), heart rate (HR), breathing-breathing interval (BBI) and heart rate variability (HRV) are the critical vital sign parameters. In this article, a novel method named adaptive separation variational mode extraction algorithm (ASVME) is proposed to accurately monitor multi-variable vital signs (MVVS) at the same time with a frequency-modulated continuous wave (FMCW) radar system in practical scenarios. Firstly, a minimum variance distortionless response (MVDR) spectrum estimation algorithm is proposed to accurately locate respiratory and heartbeat components, which can effectively restrain the influence of respiratory harmonics on HR and R-R intervals (RRI) measurements. Subsequently, an adaptive variational mode extraction (AVME) algorithm is proposed to accurately extract respiratory waves and heartbeat waves after accurate frequency location. 

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