Multiple Object Localization and Vital Sign Monitoring Using IR-UWB MIMO Radar

Shang, Xiaolei; Liu, Jian; Li, Jian

doi:10.1109/taes.2020.2990817

Cited by 53 publications

(25 citation statements)

References 41 publications

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“…In the last few years, increasing attention is being paid to MIMO radar systems, mainly because they make range and DOA estimation of multiple targets possible. The use of MIMO FMCW, IR-UWB and CW radar systems for the monitoring of vital signs has been investigated in [54][55][56][57][58], [59,60] and [61] respectively. More specifically, the use of MIMO FMCW radars operating at 77 GHz and at 120 GHz has been studied in [54][55][56] and [58], respectively, whereas the simultaneous use of two FMCW radars, each endowed with single ULA, but one operating at 24 GHz and the other one at 77 GHz, has been investigated in [57].…”

Section: Vb Estimation Of Vital Signs Of Multiple Subjects Through Mu...mentioning

confidence: 99%

See 1 more Smart Citation

Radar-based Monitoring of Vital Signs: A Tutorial Overview

Paterniani¹,

Sgreccia²,

DAVOLI³

et al. 2022

Preprint

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Section: Vb Estimation Of Vital Signs Of Multiple Subjects Through Mu...mentioning

confidence: 99%

“…[l, k] is defined by(60),l m = 21, l M = 33, K m = 32.6 (l m = 2, l M = 3, K m = 2.6) for x =TI (x =P2G); b) N 0 =512 and R m = 0.65 m, R M = 1 m have been selected for both radar systems. Note that R[k] (85) does not necessary coincide with the reference range R ref , since:…”

mentioning

confidence: 99%

Radar-based Monitoring of Vital Signs: A Tutorial Overview

Paterniani¹,

Sgreccia²,

DAVOLI³

et al. 2022

Preprint

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show abstract

“…The work in [ 31 ] deals with random body movements artifacts while driving and detects vital signs by segmenting and reconstructing vital signal based on the correlation method. The authors of [ 32 , 33 , 34 ] monitor heartbeat and breath with the target swing body back and forth. The work in [ 32 ] develops an IR-UWB radar system with MIMO prototype to detect thorax signals from both target front and the back, and an iterative adaptive approach is applied to determine respiration and heartbeat rates.…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [ 32 , 33 , 34 ] monitor heartbeat and breath with the target swing body back and forth. The work in [ 32 ] develops an IR-UWB radar system with MIMO prototype to detect thorax signals from both target front and the back, and an iterative adaptive approach is applied to determine respiration and heartbeat rates. The work in [ 33 ] presents a multi-feature alignment two-layer EEMD method to detect breath and heart rate to alleviate body fluctuation interference in the driving scenario.…”

Section: Introductionmentioning

confidence: 99%

Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Zhang

Yang

Ding

et al. 2021

Sensors

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Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

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“…To overcome the shadowing problem, this study introduces simultaneous use of multiple radar systems to perform respiratory measurements of multiple people. There have been previous studies that used multiradar systems to measure the respiration of multiple people: Shang et al [40] used two radar systems to measure two people in the presence of body motion, and Yang et al [41] used two radar systems to measure five people. In these studies, it was assumed that the relative positions and orientations of the radar systems were known in advance, and that the echoes from all target people could be measured directly by each of the radar systems without the shadowing problem.…”

Section: Introductionmentioning

confidence: 99%

Multiradar Data Fusion for Respiratory Measurement of Multiple People

2021

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This study proposes a data fusion method for multiradar systems to enable measurement of the respiration of multiple people located at arbitrary positions. Using the proposed method, the individual respiration rates of multiple people can be measured, even when echoes from some of these people cannot be received by one of the radar systems because of shadowing. In addition, the proposed method does not require information about the positions and orientations of the radar systems used because the method can estimate the layout of these radar systems by identifying multiple human targets that can be measured from different angles using multiple radar systems. When a single target person can be measured using multiple radar systems simultaneously, the proposed method selects an accurate signal from among the multiple signals based on the spectral characteristics. To verify the effectiveness of the proposed method, we performed experiments based on two scenarios with different layouts that involved seven participants and two radar systems. Through these experiments, the proposed method was demonstrated to be capable of measuring the respiration of all seven people by overcoming the shadowing issue. In the two scenarios, the average errors of the proposed method in estimating the respiration rates were 0.33 and 1.24 respirations per minute (rpm), respectively, thus demonstrating accurate and simultaneous respiratory measurements of multiple people using the multiradar system.

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Multiple Object Localization and Vital Sign Monitoring Using IR-UWB MIMO Radar

Cited by 53 publications

References 41 publications

Radar-based Monitoring of Vital Signs: A Tutorial Overview

Radar-based Monitoring of Vital Signs: A Tutorial Overview

Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Multiradar Data Fusion for Respiratory Measurement of Multiple People

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