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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Main Authors: Fatima Sekak, Kawtar Zerhouni, Fouzia Elbahhar, Madjid Haddad, Christophe Loyez, Kamel Haddadi
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/12/3396
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spelling 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
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AT madjidhaddad cyclostationarybasedvitalsignsdetectionusingmicrowaveradarat25ghz
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