Selecting Target Range with Accurate Vital Sign Using Spatial Phase Coherency of FMCW Radar

Choi, Ho-Ik; Song, Woo‐Jin; Song, Heemang; Shin, Hyun-Chool

doi:10.3390/app11104514

Cited by 10 publications

(3 citation statements)

References 52 publications

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“…As a result, FMCW has a strong anti-interference ability and the potential for monitoring multiple subjects simultaneously [ 25 , 26 ]. Effective algorithms for determining the distance between monitored subjects and radar were also developed [ 27 , 28 , 29 ]. When there are multiple individuals at the same distance from the radar, their vital signals can still be separated and monitored simultaneously with beamforming technologies [ 30 , 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring

Han

Zhai

Zhang

et al. 2023

Sensors

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Noncontact vital sign monitoring based on radar has attracted great interest in many fields. Heart Rate Variability (HRV), which measures the fluctuation of heartbeat intervals, has been considered as an important indicator for general health evaluation. This paper proposes a new algorithm for HRV monitoring in which frequency-modulated continuous-wave (FMCW) radar is used to separate echo signals from different distances, and the beamforming technique is adopted to improve signal quality. After the phase reflecting the chest wall motion is demodulated, the acceleration is calculated to enhance the heartbeat and suppress the impact of respiration. The time interval of each heartbeat is estimated based on the smoothed acceleration waveform. Finally, a joint optimization algorithm was developed and is used to precisely segment the acceleration signal for analyzing HRV. Experimental results from 10 participants show the potential of the proposed algorithm for obtaining a noncontact HRV estimation with high accuracy. The proposed algorithm can measure the interbeat interval (IBI) with a root mean square error (RMSE) of 14.9 ms and accurately estimate HRV parameters with an RMSE of 3.24 ms for MEAN (the average value of the IBI), 4.91 ms for the standard deviation of normal to normal (SDNN), and 9.10 ms for the root mean square of successive differences (RMSSD). These results demonstrate the effectiveness and feasibility of the proposed method in emotion recognition, sleep monitoring, and heart disease diagnosis.

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Section: Introductionmentioning

confidence: 99%

A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring

Han

Zhai

Zhang

et al. 2023

Sensors

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“…Detecting driver breathing abnormalities and drowsy driving in advance and implementing real-time measurement can thus prevent major accidents. A highly accurate driver vital monitoring study becomes necessary in this regard [3,4].…”

Section: Introductionmentioning

confidence: 99%

Movement Compensated Driver’s Respiratory Rate Extraction

Yoo

Shin

2022

Applied Sciences

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In non-contact vital sign monitoring using radar, radar signal distorted by the surrounding unspecified factors is unsuitable for monitoring vital signs. In order to monitor vital signs accurately, it is essential to compensate for distortion of radar signals caused by surrounding environmental factors. In this paper, we propose a driver vital signal compensation method in driving situations, including the driver’s movements using a frequency-modulated continuous-wave (FMCW) radar. Driver’s movement is quantified from the radar signal and used to set a distortion signal compensation index to compensate for the signal distortion induced in the driving situation that the driver’s movement occurs. The experimental results show that the respiration rate estimated from the radar signal compensated through the proposed method is similar to the actual respiration rate than from the signal before calibration. These results confirm the possibility of using the proposed method in a non-statistic situation and effectiveness in estimating respiration rate reflecting human movement in monitoring vital signs using FMCW radar.

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“…When the target keeps still, many remote sensing solutions are provided based on various radar systems, mainly consisting of the Continuous Wave (CW) radar [6,7], Frequency Modulated Continuous Wave (FMCW) radar [8][9][10][11], and Impulse Radio Ultra-WideBand (IR-UWB) radar [12][13][14][15][16][17]. CW radar is not only hindered by the calibration difficulty caused by the null point issue, but also lacks ability of range detection, which brings challenge for vital signs monitoring during PA.…”

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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Selecting Target Range with Accurate Vital Sign Using Spatial Phase Coherency of FMCW Radar

Cited by 10 publications

References 52 publications

A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring

A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring

Movement Compensated Driver’s Respiratory Rate Extraction

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

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