Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz
Non-contact detection and estimation of vital signs such as respiratory and cardiac frequencies is a powerful tool for surveillance applications. In particular, the continuous wave bio-radar has been widely investigated to determine the physiological parameters in a non-contact manner. Since the RF-...
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doaj-8f443a0ae34e4aedadb2edacbafed89c2020-11-25T03:03:28ZengMDPI AGSensors1424-82202020-06-01203396339610.3390/s20123396Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHzFatima Sekak0Kawtar Zerhouni1Fouzia Elbahhar2Madjid Haddad3Christophe Loyez4Kamel Haddadi5CNRS, UMR 8520–IEMN groupe CSAM (Systems Circuits Microwave Applications), University of Lille, F-59000 Lille, FranceGroupe LEOST (Electronic Wave and Signal Laboratory for Transport), University of Gustave Eiffel, F-59666 Villeneuve d’ Ascq, FranceGroupe LEOST (Electronic Wave and Signal Laboratory for Transport), University of Gustave Eiffel, F-59666 Villeneuve d’ Ascq, FranceSegula Engineering France, 92500 Rueil-Malmaison, FranceCNRS, UMR 8520–IEMN groupe CSAM (Systems Circuits Microwave Applications), University of Lille, F-59000 Lille, FranceCNRS, UMR 8520–IEMN groupe CSAM (Systems Circuits Microwave Applications), University of Lille, F-59000 Lille, FranceNon-contact detection and estimation of vital signs such as respiratory and cardiac frequencies is a powerful tool for surveillance applications. In particular, the continuous wave bio-radar has been widely investigated to determine the physiological parameters in a non-contact manner. Since the RF-reflected signal from the human body is corrupted by noise and random body movements, traditional Fourier analysis fails to detect the heart and breathing frequencies. In this effort, cyclostationary analysis has been used to improve the radar performance for non-invasive measurement of respiratory rate and heart rate. However, the preliminary works focus only on one frequency and do not include the impact of attenuation and random movement of the body in the analysis. Hence in this paper, we evaluate the impact of distance and noise on the cyclic features of the reflected signal. Furthermore, we explore the assessment of second order cyclostationary signal processing performance by developing the cyclic mean, the conjugate cyclic autocorrelation and the cyclic cumulant. In addition, the analysis is carried out using a reduced number of samples to reduce the response time. Implementation of the cyclostationary technique using a bi-static radar configuration at 2.5 GHz is shown as an example to demonstrate the proposed approach.https://www.mdpi.com/1424-8220/20/12/3396microwave radarvital signsrespiration ratehearth ratecyclostationarycyclic moment |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fatima Sekak Kawtar Zerhouni Fouzia Elbahhar Madjid Haddad Christophe Loyez Kamel Haddadi |
spellingShingle |
Fatima Sekak Kawtar Zerhouni Fouzia Elbahhar Madjid Haddad Christophe Loyez Kamel Haddadi Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz Sensors microwave radar vital signs respiration rate hearth rate cyclostationary cyclic moment |
author_facet |
Fatima Sekak Kawtar Zerhouni Fouzia Elbahhar Madjid Haddad Christophe Loyez Kamel Haddadi |
author_sort |
Fatima Sekak |
title |
Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz |
title_short |
Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz |
title_full |
Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz |
title_fullStr |
Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz |
title_full_unstemmed |
Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz |
title_sort |
cyclostationary-based vital signs detection using microwave radar at 2.5 ghz |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-06-01 |
description |
Non-contact detection and estimation of vital signs such as respiratory and cardiac frequencies is a powerful tool for surveillance applications. In particular, the continuous wave bio-radar has been widely investigated to determine the physiological parameters in a non-contact manner. Since the RF-reflected signal from the human body is corrupted by noise and random body movements, traditional Fourier analysis fails to detect the heart and breathing frequencies. In this effort, cyclostationary analysis has been used to improve the radar performance for non-invasive measurement of respiratory rate and heart rate. However, the preliminary works focus only on one frequency and do not include the impact of attenuation and random movement of the body in the analysis. Hence in this paper, we evaluate the impact of distance and noise on the cyclic features of the reflected signal. Furthermore, we explore the assessment of second order cyclostationary signal processing performance by developing the cyclic mean, the conjugate cyclic autocorrelation and the cyclic cumulant. In addition, the analysis is carried out using a reduced number of samples to reduce the response time. Implementation of the cyclostationary technique using a bi-static radar configuration at 2.5 GHz is shown as an example to demonstrate the proposed approach. |
topic |
microwave radar vital signs respiration rate hearth rate cyclostationary cyclic moment |
url |
https://www.mdpi.com/1424-8220/20/12/3396 |
work_keys_str_mv |
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