Dynamic Estimation of Vital Signs with mm-wave FMCW Radar

Conference paper (2021)

Authors

Guigeng Su Student
N. Petrov Microwave Sensing, Signals & Systems - EEMCS
Alexander Yarovoy Microwave Sensing, Signals & Systems - EEMCS
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
Copyright: © 2021 Guigeng Su, N. Petrov, Alexander Yarovoy
DOI
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https://doi.org/10.1109/EuRAD48048.2021.00060
Vital signs Sequential estimation Extended Kalman filter (EKF)
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Published Date

2021

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

Abstract

In this paper, we propose a method for continuous monitoring of vital signs-in particular, respiration frequency-with a commercial mm-wave radar. The nearly constant frequency (NCF) model is adopted to represent chest displacement due to respiration and simulate radar response. Based on this model, an extended Kalman filter (EKF) based estimator is developed to track the breathing frequency of a person. The impact of dynamic model parameters is investigated in numerical simulation. The possibility to track breathing frequency with the proposed method is demonstrated by experimental data processing.

Files

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