Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

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.

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

Sensors ◽

10.3390/s21196443 ◽

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.

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

Sensors ◽

10.3390/s21072412 ◽

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.

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

npj Digital Medicine ◽

10.1038/s41746-021-00543-z ◽

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.

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

Sensors ◽

10.3390/s20123489 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3489 ◽

Cited By ~ 2

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.

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

Applied Sciences ◽

10.3390/app11104514 ◽

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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Asynchronous electric field visualization using an integrated multichannel electro-optic probe

Scientific Reports ◽

10.1038/s41598-020-73538-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Shintaro Hisatake ◽

Junpei Kamada ◽

Yuya Asano ◽

Hirohisa Uchida ◽

Makoto Tojo ◽

...

Keyword(s):

Continuous Wave ◽

Near Field ◽

Horn Antenna ◽

Optimal Placement ◽

Radar Signal ◽

Radiation Patterns ◽

Practical Applications ◽

Fmcw Radar ◽

Realistic Situation ◽

Reference Probe

Abstract The higher the frequency, the more complex the scattering, diffraction, multiple reflection, and interference that occur in practical applications such as radar-installed vehicles and transmitter-installed mobile modules, etc. Near-field measurement in “real situations” is important for not only investigating the origin of unpredictable field distortions but also maximizing the system performance by optimal placement of antennas, modules, etc. Here, as an alternative to the previous vector-network-analyzer-based measurement, we propose a new asynchronous approach that visualizes the amplitude and phase distributions of electric near-fields three-dimensionally without placing a reference probe at a fixed point or plugging a cable to the RF source to be measured. We demonstrate the visualization of a frequency-modulated continuous wave (FMCW) signal (24 GHz ± 40 MHz, modulation cycle: 2.5 ms), and show that the measured radiation patterns of a standard horn antenna agree well with the simulation results. We also demonstrate a proof-of-concept experiment that imitates a realistic situation of a bumper installed vehicle to show how the bumper alters the radiation patterns of the FMCW radar signal. The technique is based on photonics and enables measuring in the microwave to millimeter-wave range.

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Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit

npj Digital Medicine ◽

10.1038/s41746-019-0199-5 ◽

2019 ◽

Vol 2 (1) ◽

Cited By ~ 7

Author(s):

Mauricio Villarroel ◽

Sitthichok Chaichulee ◽

João Jorge ◽

Sara Davis ◽

Gabrielle Green ◽

...

Keyword(s):

Intensive Care Unit ◽

Heart Rate ◽

Respiratory Rate ◽

Preterm Infants ◽

Neonatal Intensive Care ◽

Mean Absolute Error ◽

Vital Signs ◽

Absolute Error ◽

Video Camera ◽

The Mean

AbstractThe implementation of video-based non-contact technologies to monitor the vital signs of preterm infants in the hospital presents several challenges, such as the detection of the presence or the absence of a patient in the video frame, robustness to changes in lighting conditions, automated identification of suitable time periods and regions of interest from which vital signs can be estimated. We carried out a clinical study to evaluate the accuracy and the proportion of time that heart rate and respiratory rate can be estimated from preterm infants using only a video camera in a clinical environment, without interfering with regular patient care. A total of 426.6 h of video and reference vital signs were recorded for 90 sessions from 30 preterm infants in the Neonatal Intensive Care Unit (NICU) of the John Radcliffe Hospital in Oxford. Each preterm infant was recorded under regular ambient light during daytime for up to four consecutive days. We developed multi-task deep learning algorithms to automatically segment skin areas and to estimate vital signs only when the infant was present in the field of view of the video camera and no clinical interventions were undertaken. We propose signal quality assessment algorithms for both heart rate and respiratory rate to discriminate between clinically acceptable and noisy signals. The mean absolute error between the reference and camera-derived heart rates was 2.3 beats/min for over 76% of the time for which the reference and camera data were valid. The mean absolute error between the reference and camera-derived respiratory rate was 3.5 breaths/min for over 82% of the time. Accurate estimates of heart rate and respiratory rate could be derived for at least 90% of the time, if gaps of up to 30 seconds with no estimates were allowed.

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A Novel Vital-Sign Sensing Algorithm for Multiple Subjects Based on 24-GHz FMCW Doppler Radar

Remote Sensing ◽

10.3390/rs11101237 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1237 ◽

Cited By ~ 15

Author(s):

Hyunjae Lee ◽

Byung-Hyun Kim ◽

Jin-Kwan Park ◽

Jong-Gwan Yook

Keyword(s):

Vital Sign ◽

Continuous Wave ◽

Doppler Radar ◽

Spectral Estimation ◽

Estimation Method ◽

Vital Signs ◽

Phase Information ◽

Multiple Targets ◽

Wave Radar ◽

24 Ghz

A novel non-contact vital-sign sensing algorithm for use in cases of multiple subjects is proposed. The approach uses a 24 GHz frequency-modulated continuous-wave Doppler radar with the parametric spectral estimation method. Doppler processing and spectral estimation are concurrently implemented to detect vital signs from more than one subject, revealing excellent results. The parametric spectral estimation method is utilized to clearly identify multiple targets, making it possible to distinguish multiple targets located less than 40 cm apart, which is beyond the limit of the theoretical range resolution. Fourier transformation is used to extract phase information, and the result is combined with the spectral estimation result. To eliminate mutual interference, the range integration is performed when combining the range and phase information. By considering breathing and heartbeat periodicity, the proposed algorithm can accurately extract vital signs in real time by applying an auto-regressive algorithm. The capability of a contactless and unobtrusive vital sign measurement with a millimeter wave radar system has innumerable applications, such as remote patient monitoring, emergency surveillance, and personal health care.

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Semi-Physical Simulation System for FMCW Radar

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.135-136.886 ◽

2011 ◽

Vol 135-136 ◽

pp. 886-892

Author(s):

Wen Hui Chen ◽

Xin Xi Meng ◽

Xiao Min Liu

Keyword(s):

Power Consumption ◽

Low Power ◽

Physical Simulation ◽

Continuous Wave ◽

Low Cost ◽

Simulation System ◽

Radar Signal ◽

Low Power Consumption ◽

Fmcw Radar ◽

Data Process

In order to process and analyze the signal of frequency modulated continuous wave (FMCW) radar, a radar semi-physical simulation(RSPS) system based on STM32F103VE6 chip is designed in this paper. By designing the hardware and software of system, the RSPS system can process the radar signal, detect the target, verify the data process algorithm and display the result on TFT-LCD screen. In addition, the collected data can be uploaded to PC by RS-232 interfaces which improves the reliability, stability and practicability of system. The waveform and spectrum maps are utilized to show the feasibility of RSPS system in analysing FMCW radar signal. Experimental results show that this system has many advantages, such as multifunction, low power consumption and low cost.

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Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors

Sensors ◽

10.3390/s21175735 ◽

2021 ◽

Vol 21 (17) ◽

pp. 5735

Author(s):

Somayyeh Chamaani ◽

Alireza Akbarpour ◽

Marko Helbig ◽

Jürgen Sachs

Keyword(s):

Vital Sign ◽

Continuous Wave ◽

Vital Signs ◽

Matrix Pencil ◽

Ultra Wideband ◽

Frequency Resolution ◽

High Temporal Resolution ◽

Matrix Pencil Method ◽

Mode Decomposition ◽

Microwave Sensors

Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method.

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