scholarly journals Developing of Algorithms Monitoring Heartbeat and Respiration Rate of a Seated Person with an FMCW Radar

2021 ◽  
Vol 19 ◽  
pp. 195-206
Author(s):  
Lorenz J. Dirksmeyer ◽  
Aly Marnach ◽  
Daniel Schmiech ◽  
Andreas R. Diewald
Keyword(s):  
Respiration Rate ◽  
Continuous Wave ◽  
Frequency Estimation ◽  
Wavelet Packet ◽  
Vital Signs ◽  
Wave Mode ◽  
Fine Tuning ◽  
Fmcw Radar ◽  
Real Time Visualization ◽  
Spectral Frequency

Abstract. With a radar working in the 24 GHz ISM-band in a frequency modulated continuous wave mode the major vital signs heartbeat and respiration rate are monitored. The observation is hereby contactless with the patient sitting straight up in a distance of 1–2 m to the radar. Radar and sampling platform are components developed internally in the university institution. The communication with the radar is handled with MATLAB via TCP/IP. The signal processing and real-time visualization is developed in MATLAB, too. Cornerstone of this publication are the wavelet packet transformation and a spectral frequency estimation for vital sign calculation. The wavelet transformation allows a fine tuning of frequency subspaces, separating the heartbeat signal from the respiration and more important from noise and other movement. Heartbeat and respiration are monitored independently and compared to parallel recorded ECG-data.

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 Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion

2021 ◽  
Vol 13 (18) ◽  
pp. 3791
Author(s):  
Xiuzhu Yang ◽  
Xinyue Zhang ◽  
Yi Ding ◽  
Lin Zhang
Keyword(s):  
Data Fusion ◽  
Vital Sign ◽  
Continuous Wave ◽  
Short Term Memory ◽  
Wavelet Packet ◽  
Vital Signs ◽  
Radar Data ◽  
Activity Monitoring ◽  
Ultra Wideband ◽  
Additional Information

The monitoring of human activity and vital signs plays a significant role in remote health-care. Radar provides a non-contact monitoring approach without privacy and illumination concerns. However, multiple people in a narrow indoor environment bring dense multipaths for activity monitoring, and the received vital sign signals are heavily distorted with body movements. This paper proposes a framework based on Frequency Modulated Continuous Wave (FMCW) and Impulse Radio Ultra-Wideband (IR-UWB) radars to address these challenges, designing intelligent spatial-temporal information fusion for activity and vital sign monitoring. First, a local binary pattern (LBP) and energy features are extracted from FMCW radar, combined with the wavelet packet transform (WPT) features on IR-UWB radar for activity monitoring. Then the additional information guided fusing network (A-FuseNet) is proposed with a modified generative and adversarial structure for vital sign monitoring. A Cascaded Convolutional Neural Network (CCNN) module and a Long Short Term Memory (LSTM) module are designed as the fusion sub-network for vital sign information extraction and multisensory data fusion, while a discrimination sub-network is constructed to optimize the fused heartbeat signal. In addition, the activity and movement characteristics are introduced as additional information to guide the fusion and optimization. A multi-radar dataset with an FMCW and two IR-UWB radars in a cotton tent, a small room and a wide lobby is constructed, and the accuracies of activity and vital sign monitoring achieve 99.9% and 92.3% respectively. Experimental results demonstrate the superiority and robustness of the proposed framework.

scholarly journals Radar Recorded Child Vital Sign Public Dataset and Deep Learning-Based Age Group Classification Framework for Vehicular Application

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2412
Author(s):  
Sungwon Yoo ◽  
Shahzad Ahmed ◽  
Sun Kang ◽  
Duhyun Hwang ◽  
Jungjun Lee ◽  
...  
Keyword(s):  
Vital Sign ◽  
Continuous Wave ◽  
Age Groups ◽  
Vital Signs ◽  
Group Classification ◽  
Age Group ◽  
Smart Vehicles ◽  
Fmcw Radar ◽  
Wide Range ◽  
Age Group Classification

The ongoing intense development of short-range radar systems and their improved capability of measuring small movements make these systems reliable solutions for the extraction of human vital signs in a contactless fashion. The continuous contactless monitoring of vital signs can be considered in a wide range of applications, such as remote healthcare solutions and context-aware smart sensor development. Currently, the provision of radar-recorded datasets of human vital signs is still an open issue. In this paper, we present a new frequency-modulated continuous wave (FMCW) radar-recorded vital sign dataset for 50 children aged less than 13 years. A clinically approved vital sign monitoring sensor was also deployed as a reference, and data from both sensors were time-synchronized. With the presented dataset, a new child age-group classification system based on GoogLeNet is proposed to develop a child safety sensor for smart vehicles. The radar-recorded vital signs of children are divided into several age groups, and the GoogLeNet framework is trained to predict the age of unknown human test subjects.

scholarly journals High Accuracy Motion Detection Algorithm via ISM Band FMCW Radar

2021 ◽  
Vol 14 (1) ◽  
pp. 58
Author(s):  
Kui Qu ◽  
Rongfu Zhang ◽  
Zhijun Fang
Keyword(s):  
Fourier Transform ◽  
Continuous Wave ◽  
Frequency Estimation ◽  
Detection Algorithm ◽  
Center Frequency ◽  
Dc Offset ◽  
Fmcw Radar ◽  
Ism Band ◽  
Time Motion ◽  
Stationary Objects

The conventional frequency modulated continuous wave (FMCW) radar accuracy range detection algorithm is based on the frequency estimation and additional phase evaluation which contains Fourier transform and frequency refining analysis in each chirp, so it has the disadvantages of being computationally expensive, and not being suitable for real-time motion measurement. In addition, if there are other objects near the target, the spectra of the clutter and the target will be adjacent and affect each other, making it more challenging to estimate the frequency of the target. In this paper, the analytical expression of the Fourier transform of the beat signal is presented and it can be seen that spectrum leakage makes the phase of Fourier transform no longer consistent with the real phase of signal. The change regularities of real and imaginary parts of Fourier transform are studied, and the corrected phase of ellipse approximation is given in the industrial, scientific, and medical (ISM) band. Accurate displacement can be obtained by accurate phase. The algorithm can filter the direct current (DC) offset which is mainly caused by stationary objects. The performance of the algorithm is evaluated by a radar system whose center frequency is 24.075 GHz and the bandwidth is 0.15 GHz; the measurement accuracy of displacement is 0.087 mm and the accuracy of distance is 0.043 m.

scholarly journals Multi-target vital signs detection using frequency-modulated continuous wave radar

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yong Wang ◽  
Yuzhu Shui ◽  
Xiaobo Yang ◽  
Zhaoyu Li ◽  
Wen Wang
Keyword(s):  
Continuous Wave ◽  
Matching Pursuit ◽  
Three Dimensional ◽  
Vital Signs ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Discrete Wavelet ◽  
Fmcw Radar ◽  
Wave Radar ◽  
Spatially Distributed

AbstractRespiration and heartbeats rates are important physiological assessment indicators that provide valid prior-knowledge for the diagnosis of numerous diseases. However, most of the current research focuses on the vital signs measurement of single target, and multi-target vital signs detection has not received much attention. In this paper, we use frequency-modulated continuous wave (FMCW) radar to measure the vital signs signals of multi-target. First, we apply the three-dimensional fast Fourier transform (3D-FFT) method to separate multiple targets and get their distance and azimuth information. Subsequently, the linear constrained minimum variance-based adaptive beamforming (LCMV-ADBF) technique is proposed to form a spatially distributed beams on the targets of interest directions. Finally, a compressive sensing based on orthogonal matching pursuit (CS-OMP) method and rigrsure adaptive soft threshold noise reduction based on discrete wavelet transform (RA-DWT) method are present to extract the respiratory and heartbeat signals. We perform tests in a real experimental environment and compare the proposed method with reference devices. The results show that the degrees of agreement for respiratory and heartbeat are 89% and 87%, respectively, for two human targets. The level of agreement for respiratory and heartbeat is 87% and 85%, respectively, for three human targets, proving the effectiveness of the proposed method.

scholarly journals An FMCW Radar for Localization and Vital Signs Measurement for Different Chest Orientations

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3489 ◽  
Author(s):  
Giulia Sacco ◽  
Emanuele Piuzzi ◽  
Erika Pittella ◽  
Stefano Pisa
Keyword(s):  
Respiratory Rate ◽  
Assisted Living ◽  
Continuous Wave ◽  
Low Cost ◽  
Ambient Assisted Living ◽  
Vital Signs ◽  
Side Lobe ◽  
Radar Signal ◽  
Side Lobe Level ◽  
Fmcw Radar

This work tests the ability of a frequency-modulated continuous wave (FMCW) radar to measure the respiratory rate and the heartbeat of a subject in challenging indoor scenarios. To simulate a realistic configuration for ambient assisted living (AAL) applications, in which the thorax orientation towards the antenna is typically unknown, four different scenarios were considered. Measurements were performed on five volunteers positioned with the chest, left, back, and right side facing the antenna, respectively. The 5.8 GHz radar and the antennas used for the measurements were suitably designed for the considered application. To obtain a low cost and compact system, series-fed arrays were preferred over other antenna topologies. The geometry of the patches was opportunely shaped to reduce the side lobe level (SLL) and increase the bandwidth, thus ensuring good system performances. In all scenarios, the vital signs extracted from the radar signal were compared with the ones collected by a photoplethysmograph and a respiratory belt, used as references. A statistical analysis of the measured data on the different subjects and orientations was performed, showing that the radar was able to measure with high accuracy both the respiratory rate and the heartbeat in all considered configurations.

scholarly journals Experimental Comparison of IR-UWB Radar and FMCW Radar for Vital Signs

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6695
Author(s):  
Dingyang Wang ◽  
Sungwon Yoo ◽  
Sung Ho Cho
Keyword(s):  
Continuous Wave ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Experimental Comparison ◽  
Distance Information ◽  
Mimo Antenna ◽  
Fmcw Radar ◽  
Uwb Radar ◽  
Sign Detection ◽  
Detection Capabilities

In this paper, we compare the performances of impulse radio ultra-wideband (IR-UWB) and frequency modulation continuous wave (FMCW) radars in measuring noncontact vital signs such as respiration rate and heart rate. These two type radars have been widely used in various fields and have shown their applicability to extract vital signs in noncontact ways. IR-UWB radar can extract vital signs using distance information. On the other hand, FMCW radar requires phase information to estimate vital signs, and the result can be enhanced with Multi-input Multi-output (MIMO) antenna topologies. By using commercial radar chipsets, the operation of radars under different conditions and frequency bands will also affect the performance of vital sign detection capabilities. We compared the accuracy and signal-to-noise (SNR) ratios of IR-UWB and FMCW radars in various scenarios, such as distance, orientation, carotid pulse, harmonics, and obstacle penetration. In general, the IR-UWB radars offer a slightly better accuracy and higher SNR in comparison to FMCW radar. However, each radar system has its own unique advantages, with IR-UWB exhibiting fewer harmonics and a higher SNR, while FMCW can combine the results from each channel.

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

2021 ◽  
Vol 11 (10) ◽  
pp. 4514
Author(s):  
Ho-Ik Choi ◽  
Woo-Jin Song ◽  
Heemang Song ◽  
Hyun-Chool Shin
Keyword(s):  
Vital Sign ◽  
Continuous Wave ◽  
Physiological State ◽  
Vital Signs ◽  
Target Range ◽  
Human Beings ◽  
Fmcw Radar ◽  
Spatial Phase ◽  
Human Respiration ◽  
Human Body Surface

Respiration and heartbeat are basic indicators of the physiological state of human beings. Frequency-modulated continuous wave (FMCW) radar can sense micro-displacement in the human body surface without contact, and is used for vital-sign (respiration and heartbeat) monitoring. For the extraction of vital-sign, it is essential to select the target range containing vital-sign information. In this paper, we exploit the coherency of phase in different range-bins of FMCW radar to effectively select the range-bins that contain accurate signals for remote monitoring of human respiration and heartbeat. To quantify coherency, the spatial phase coherency (SPC) index is introduced. The experimental results show that the SPC can select a range-bin containing more accurate vital-sign signals than conventional methods. This result demonstrates that the proposed method is accurate for monitoring of vital signs by using FMCW radar.

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