Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars

This paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some technique...

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Main Authors: Antonio Lazaro, David Girbau, Ramon Villarino
Format: Article
Language:English
Published: MDPI AG 2014-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/14/2/2595
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author Antonio Lazaro
David Girbau
Ramon Villarino
author_facet Antonio Lazaro
David Girbau
Ramon Villarino
author_sort Antonio Lazaro
collection DOAJ
description This paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some techniques to solve several problems in these types of measurements, such as the clutter suppression, body movement and body orientation detection are described. Clutter suppression is achieved using a moving averaging filter to dynamically estimate it. The artifacts caused by body movements are removed using a threshold method before analyzing the breathing signal. The motion is detected using the time delay that maximizes the received signal after a clutter removing algorithm is applied. The periods in which the standard deviations of the time delay exceed a threshold are considered macro-movements and they are neglected. The sleep apnea intervals are detected when the breathing signal is below a threshold. The breathing rate is determined from the robust spectrum estimation based on Lomb periodogram algorithm. On the other hand the breathing signal amplitude depends on the body orientation respect to the antennas, and this could be a problem. In this case, in order to maximize the signal-to-noise ratio, multiple sensors are proposed to ensure that the backscattered signal can be detected by at least one sensor, regardless of the direction the human subject is facing. The feasibility of the system is compared with signals recorded by a microphone.
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spelling doaj.art-01b76764ae084eb3955956925319e4462022-12-22T02:17:58ZengMDPI AGSensors1424-82202014-02-011422595261810.3390/s140202595s140202595Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB RadarsAntonio Lazaro0David Girbau1Ramon Villarino2Department of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, SpainDepartment of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, SpainDepartment of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, SpainThis paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some techniques to solve several problems in these types of measurements, such as the clutter suppression, body movement and body orientation detection are described. Clutter suppression is achieved using a moving averaging filter to dynamically estimate it. The artifacts caused by body movements are removed using a threshold method before analyzing the breathing signal. The motion is detected using the time delay that maximizes the received signal after a clutter removing algorithm is applied. The periods in which the standard deviations of the time delay exceed a threshold are considered macro-movements and they are neglected. The sleep apnea intervals are detected when the breathing signal is below a threshold. The breathing rate is determined from the robust spectrum estimation based on Lomb periodogram algorithm. On the other hand the breathing signal amplitude depends on the body orientation respect to the antennas, and this could be a problem. In this case, in order to maximize the signal-to-noise ratio, multiple sensors are proposed to ensure that the backscattered signal can be detected by at least one sensor, regardless of the direction the human subject is facing. The feasibility of the system is compared with signals recorded by a microphone.http://www.mdpi.com/1424-8220/14/2/2595breathing monitoringsleep apneavital signsultra-wideband radar
spellingShingle Antonio Lazaro
David Girbau
Ramon Villarino
Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
Sensors
breathing monitoring
sleep apnea
vital signs
ultra-wideband radar
title Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
title_full Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
title_fullStr Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
title_full_unstemmed Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
title_short Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars
title_sort techniques for clutter suppression in the presence of body movements during the detection of respiratory activity through uwb radars
topic breathing monitoring
sleep apnea
vital signs
ultra-wideband radar
url http://www.mdpi.com/1424-8220/14/2/2595
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