Print Email Facebook Twitter Dynamic Estimation of Vital Signs with mm-wave FMCW Radar Title Dynamic Estimation of Vital Signs with mm-wave FMCW Radar Author Su, Guigeng (Student TU Delft) Petrov, N. (TU Delft Microwave Sensing, Signals & Systems) Yarovoy, Alexander (TU Delft Microwave Sensing, Signals & Systems) Date 2021 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. Subject extended Kalman filter (EKF)sequential estimationVital signs To reference this document use: http://resolver.tudelft.nl/uuid:f9eed9e0-a6dc-4965-b4d0-912eecdf7716 DOI https://doi.org/10.1109/EuRAD48048.2021.00060 Publisher IEEE Embargo date 2021-08-30 ISBN 9782874870613 Source EuRAD 2020 - 2020 17th European Radar Conference Event 17th European Radar Conference, EuRAD 2020, 2021-01-13 → 2021-01-15, Utrecht, Netherlands Series EuRAD 2020 - 2020 17th European Radar Conference 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. Part of collection Institutional Repository Document type conference paper Rights © 2021 Guigeng Su, N. Petrov, Alexander Yarovoy Files PDF 09337302.pdf 710.38 KB Close viewer /islandora/object/uuid:f9eed9e0-a6dc-4965-b4d0-912eecdf7716/datastream/OBJ/view