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.
| Original language | English |
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| Title of host publication | EuRAD 2020 - 2020 17th European Radar Conference |
| Publisher | IEEE |
| Pages | 206-209 |
| Number of pages | 4 |
| ISBN (Electronic) | 9782874870613 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | 17th European Radar Conference, EuRAD 2020 - Utrecht, Netherlands Duration: 13 Jan 2021 → 15 Jan 2021 |
Publication series
| Name | EuRAD 2020 - 2020 17th European Radar Conference |
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Conference
| Conference | 17th European Radar Conference, EuRAD 2020 |
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| Country/Territory | Netherlands |
| City | Utrecht |
| Period | 13/01/21 → 15/01/21 |
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-careOtherwise 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.
Keywords
- extended Kalman filter (EKF)
- sequential estimation
- Vital signs