scholarly journals A Method of UWB Radar Vital Detection Based on P Time Extraction of Strong Vital Signs

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhen Yang ◽  
Jiming Cheng ◽  
Qingjie Qi ◽  
Xin Li ◽  
Yuning Wang
Keyword(s):  
Experimental Data ◽  
Vital Sign ◽  
Vital Signs ◽  
Reference Value ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Cumulative Probability ◽  
Echo Signal ◽  
Uwb Radar ◽  
Relative Errors

The vital sign information in the echo signal of the UWB radar is weak, because of the interference of complex noise. In this paper, a method named P times extraction of strong vital signs for processing echo signals of UWB radars is proposed. Different noises can be distinguished by the cumulative probability distribution of the echo signal and using different methods for processing according to corresponding characteristics. The vital sign information which most clearly represents the trapped person is selected using P times extraction of strong vital signs; then, the respiration and heartbeat rates are extracted. At 5 different distances, multiple sets of tests were carried out on static trapped persons and micromovement trapped persons and using a computer to extract vital signs from the obtained data. Experimental data shows that the algorithm proposed in this paper can extract the respiration and heartbeat rates of trapped persons, with small relative errors and variances, and has a certain reference value for UWB radar signal processing.

scholarly journals FPGA Implementation of an Efficient FFT Processor for FMCW Radar Signal Processing

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6443
Author(s):  
Jinmoo Heo ◽  
Yongchul Jung ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Signal Processing ◽  
Detection Rate ◽  
Continuous Wave ◽  
Vital Signs ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Fmcw Radar ◽  
Design And Implementation ◽  
Fft Processor ◽  
Point Operator

This paper presents the design and implementation results of an efficient fast Fourier transform (FFT) processor for frequency-modulated continuous wave (FMCW) radar signal processing. The proposed FFT processor is designed with a memory-based FFT architecture and supports variable lengths from 64 to 4096. Moreover, it is designed with a floating-point operator to prevent the performance degradation of fixed-point operators. FMCW radar signal processing requires windowing operations to increase the target detection rate by reducing clutter side lobes, magnitude calculation operations based on the FFT results to detect the target, and accumulation operations to improve the detection performance of the target. In addition, in some applications such as the measurement of vital signs, the phase of the FFT result has to be calculated. In general, only the FFT is implemented in the hardware, and the other FMCW radar signal processing is performed in the software. The proposed FFT processor implements not only the FFT, but also windowing, accumulation, and magnitude/phase calculations in the hardware. Therefore, compared with a processor implementing only the FFT, the proposed FFT processor uses 1.69 times the hardware resources but achieves an execution time 7.32 times shorter.

scholarly journals Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6505
Author(s):  
Emmi Turppa ◽  
Juha M. Kortelainen ◽  
Oleg Antropov ◽  
Tero Kiuru
Keyword(s):  
Heart Rate ◽  
Remote Monitoring ◽  
Vital Sign ◽  
Continuous Wave ◽  
Real Life ◽  
Vital Signs ◽  
Absolute Error ◽  
Physical Contact ◽  
Radar Signal ◽  
Fmcw Radar

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

scholarly journals Preclinical evaluation of noncontact vital signs monitoring using real-time IR-UWB radar and factors affecting its accuracy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun-Young Park ◽  
Yonggu Lee ◽  
Ran Heo ◽  
Hyun-Kyung Park ◽  
Seok-Hyun Cho ◽  
...  
Keyword(s):  
Real Time ◽  
Vital Sign ◽  
Vital Signs ◽  
Embedded Processors ◽  
Sitting Position ◽  
Mixed Effect ◽  
Factors Affecting ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
The Absolute

AbstractRecently, noncontact vital sign monitors have attracted attention because of issues related to the transmission of contagious diseases. We developed a real-time vital sign monitor using impulse-radio ultrawideband (IR-UWB) radar with embedded processors and software; we then evaluated its accuracy in measuring heart rate (HR) and respiratory rate (RR) and investigated the factors affecting the accuracy of the radar-based measurements. In 50 patients visiting a cardiology clinic, HR and RR were measured using IR-UWB radar simultaneously with electrocardiography and capnometry. All patients underwent HR and RR measurements in 2 postures—supine and sitting—for 2 min each. There was a high agreement between the RR measured using radar and capnometry (concordance correlation coefficient [CCC] 0.925 [0.919–0.926]; upper and lower limits of agreement [LOA], − 2.21 and 3.90 breaths/min). The HR measured using radar was also in close agreement with the value measured using electrocardiography (CCC 0.749 [0.738–0.760]; upper and lower LOA, − 12.78 and 15.04 beats/min). Linear mixed effect models showed that the sitting position and an HR < 70 bpm were associated with an increase in the absolute biases of the HR, whereas the sitting position and an RR < 18 breaths/min were associated with an increase in the absolute biases of the RR. The IR-UWB radar sensor with embedded processors and software can measure the RR and HR in real time with high precision. The sitting position and a low RR or HR were associated with the accuracy of RR and HR measurement, respectively, using IR-UWB radar.

scholarly journals Non-contact physiological monitoring of post-operative patients in the intensive care unit

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
João Jorge ◽  
Mauricio Villarroel ◽  
Hamish Tomlinson ◽  
Oliver Gibson ◽  
Julie L. Darbyshire ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Vital Sign ◽  
Vital Signs ◽  
Reference Value ◽  
Absolute Error ◽  
Video Camera ◽  
Clinical Observations ◽  
Operative Care ◽  
Respiratory Events

AbstractProlonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

A Method for Ultrasonic Characterization of Density, Thickness and Velocity of Homogeneous Coating

2011 ◽  
Vol 675-677 ◽  
pp. 1217-1220 ◽  
Author(s):  
Y. Zhao ◽  
Zhen Yue Ma ◽  
Li Lin ◽  
X.M. Li ◽  
M.K. Lei
Keyword(s):  
Experimental Data ◽  
Amplitude Spectrum ◽  
Reference Value ◽  
Nondestructive Method ◽  
Inverse Algorithm ◽  
Ultrasonic Characterization ◽  
Ultrasonic Reflection Coefficient ◽  
Relative Errors

This paper provides a nondestructive method for determination of the density, thickness and velocity of homogeneous coating from an inversion of experimental ultrasonic reflection coefficient amplitude spectrum (URCAS). The detailed analyses of the inverse algorithm and sensitivity of URCAS to the density, thickness and velocity are presented, and the sensitivity is identified as a basis for selecting the experimental data used in inversion. An example of the method and experimental measurement for comparison was given for an epoxy coating with the thickness of 0.277 mm. The relative errors between the inversion and reference value of the density, thickness and velocity were found to be 0.5 %, 3.97 %, and 0.97 %, respectively.

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