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ASVME
- Citation Author(s):
- Submitted by:
- zhen yang
- Last updated:
- Mon, 10/21/2024 - 05:51
- DOI:
- 10.21227/hs58-pq35
- License:
10 Views- Categories:
- Keywords:
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.
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.
