Dynamic Estimation of Vital Signs with mm-wave FMCW Radar

Conference Paper (2021)
Author(s)

Guigeng Su (Student TU Delft)

N Petrov (TU Delft - Microwave Sensing, Signals & Systems)

A.G. Yarovyi (TU Delft - Microwave Sensing, Signals & Systems)

Microwave Sensing, Signals & Systems
Copyright
© 2021 Guigeng Su, N. Petrov, Alexander Yarovoy
DOI related publication
https://doi.org/10.1109/EuRAD48048.2021.00060
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Guigeng Su, N. Petrov, Alexander Yarovoy
Microwave Sensing, Signals & Systems
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
206-209
ISBN (electronic)
9782874870613
Reuse Rights

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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.

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