Non-contact Vital Sign Monitoring Research Articles

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

We consider 2-D localization and noncontact vital sign monitoring (i.e., determining the 2-D locations and estimating the rates of respiration and heartbeat) of multiple human objects via developing an impulse radio ultra-wideband (IR-UWB) distributed multi-input multi-output (MIMO) prototype radar system. A modified back projection algorithm is used to localize multiple objects. We also formulate the chest skin range displacement estimation problem caused by respiration and heartbeat into a sinusoidal frequency estimation problem, which can be solved efficiently via the fast Fourier transform method. Then, the robust, high resolution, and low sidelobe iterative adaptive approach (IAA) is adopted to obtain the IAA spectrum of the chest skin range displacement signal. Both respiration and heartbeat rates can be reliably determined from the IAA spectral estimates. Further, we solve the random body movement problem by developing a 2 × 2 IR-UWB distributed MIMO prototype radar system to obtain measurements from both the front and back of the human torso simultaneously. Finally, numerical and experimental results based on the prototype hardware radar systems we develop are presented to demonstrate the performances of the proposed 2-D localization and noncontact vital sign monitoring systems and the corresponding algorithms.

Non-Contact Vital Signs Monitoring Through Visible Light Sensing

This paper presents a non-contact vital signs (respiration and heartbeat) monitoring system that utilizes visible light sensing (VLS) technology. We have for the first time demonstrated the ability to wirelessly (non-contact) sense vital signs using only reflected incoherent light signals from a human subject. The VLS-based system is implemented by using simple visible light source, photodetector and data acquisition/processing unit, and is used with the developed signal processing algorithms to turn slight variations in reflected light power into accurate measurements of respiration and heart rate. To assess the accuracy of our method, the results were compared with reliable measurements using a contact-based monitoring device (ground truth). More than 94% of accuracy was observed in test results including both breathing and heartbeat rates in different scenarios as compared to the state-of-the-art baseline methods such as contact-based vitals monitoring devices. These competitive results have demonstrated that VLS-based vitals monitoring innovation is indeed a viable, powerful, attractive, low-cost and safe method. This study represents a substantive departure from the traditional ways of doing non-contact vitals monitoring methods (e.g., radio-frequency-based radars and imaging-based cameras) and is poised to make big contributions to this area. Since vital signs monitoring is a ubiquitous element of medicine, this work would also impact the entire health care community, from patients in their homes, to doctor’s offices, to large medical institutions and industries. This technology has potential to address numerous conditions and situations in which vital signs are critical indicators such as sleep apnea and human-computer-interaction applications.

Non-Contact Vital Signs Monitoring of Dog and Cat Using a UWB Radar.

Simple SummaryIn this paper, we presented a new non-contact method to measure the vital signs of at-rest pets, where the ultra-wideband radar was applied for previously unachievable sensing ability and testing convenience. The proposed scheme did not interfere with the daily rhythm of the pet being tested; most subjects would not even notice the ongoing real-time monitoring due to the larger measurement coverage of the radar sensor. Through this work, we provided an innovative tool to promote not only the measurement of pet vital signs but also the improvement of animal welfare to prevent invasive, dangerous, and unacceptable contact measurement techniques, such as anesthesia, hair removal, and surgical implants. In addition, the proposed method could realize the daily vital signs measurement and sleep monitoring of dogs and cats, which is important for the diagnosis and timely treatment of pet diseases.As pets are considered members of the family, their health has received widespread attention. Since pets cannot talk and complain when they feel uncomfortable, monitoring vital signs becomes very helpful in disease detection, as well as observing their progression and response to treatment. In this study, we proposed an ultra-wideband radar-based, non-contact animal vital sign monitoring scheme that could monitor the breathing and heart rate of a pet in real-time. The primary advantage of the ultra-wideband radar was its ability to operate remotely without electrodes or wires and through any clothing or fur. Because of the existing noise and clutter in non-contact detection, background noise removal was applied. Furthermore, the respiration rate was directly obtained through spectrum analysis, while the heartbeat signal was extracted by the variational mode decomposition algorithm. By using electrocardiogram measurements, we verified the accuracy of the radar technology in detecting the anesthetized animals’ respiratory rate and heart rate. Besides, three beagles and five cats in a non-sedated state were measured by radar and contact pressure sensors simultaneously; the experimental results showed that radar could effectively measure the respiration of cats and dogs, and the accuracy rate was over 95%. Due to its excellent performance, the proposed method has the potential to become a new choice in application scenarios, such as pet sleep monitoring and health assessment.

Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning

Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO2), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospital ward, the main challenges in the development of continuous and robust non-contact monitoring techniques are the identification of time periods and the segmentation of skin regions of interest (ROIs) from which vital signs can be estimated. We propose a deep learning framework to tackle these challenges. Approach: This paper presents two convolutional neural network (CNN) models. The first network was designed for detecting the presence of a patient and segmenting the patient’s skin area. The second network combined the output from the first network with optical flow for identifying time periods of clinical intervention so that these periods can be excluded from the estimation of vital signs. Both networks were trained using video recordings from a clinical study involving 15 pre-term infants conducted in the high dependency area of the neonatal intensive care unit (NICU) of the John Radcliffe Hospital in Oxford, UK. Main results: Our proposed methods achieved an accuracy of 98.8% for patient detection, a mean intersection-over-union (IOU) score of 88.6% for skin segmentation and an accuracy of 94.5% for clinical intervention detection using two-fold cross validation. Our deep learning models produced accurate results and were robust to different skin tones, changes in light conditions, pose variations and different clinical interventions by medical staff and family visitors. Significance: Our approach allows cardio-respiratory signals to be continuously derived from the patient’s skin during which the patient is present and no clinical intervention is undertaken.

Method for Distinguishing Humans and Animals in Vital Signs Monitoring Using IR-UWB Radar.

Radar has been widely applied in many scenarios as a critical remote sensing tool for non-contact vital sign monitoring, particularly for sleep monitoring and heart rate measurement within the home environment. For non-contact monitoring with radar, interference from house pets is an important issue that has been neglected in the past. Many animals have respiratory frequencies similar to those of humans, and they are easily mistaken for human targets in non-contact monitoring, which would trigger a false alarm because of incorrect physiological parameters from the animal. In this study, humans and common pets in families, such as dogs, cats, and rabbits, were detected using an impulse radio ultrawideband (IR-UWB) radar, and the echo signals were analyzed in the time and frequency domains. Subsequently, based on the distinct in-body structure between humans and animals, we propose a parameter, the respiratory and heartbeat energy ratio (RHER), which reflects the contribution rate of breathing and heartbeat in the detected vital signs. Combining this parameter with the energy index, we developed a novel scheme to distinguish between humans and animals. In the developed scheme, after background noise removal and direct-current component suppression, an energy indicator is used to initially identify the target. The signal is then decomposed using a variational mode decomposition algorithm, and the variational intrinsic mode functions that represent human respiration and heartbeat components are obtained and utilized to calculate the RHER parameter. Finally, the RHER index is applied to rapidly distinguish between humans and animals. Our experimental results demonstrate that the proposed approach more effectively distinguishes between humans and animals in terms of monitoring vital signs than the existing methods. Furthermore, its rapidity and need for only minimal calculation resources enable it to meet the needs of real-time monitoring.

Contactless Respiration and Heartbeat Monitoring of Multiple People Using a 2-D Imaging Radar.

Non-contact vital sign monitoring of multiple people can be realized using a radar sensor that is able to provide a high resolution two-dimensional image of the monitored area. This is particularly user-friendly, since no electrodes have to be attached to the body, which is important especially in view of applications like monitoring neonates or burn victims. There are many further applications of remote cardiopulmonary monitoring in the area of home health care, driver monitoring, sleep monitoring, or even monitoring of arrested people in a prison cell. The radar is able to measure the tiny movements of the chest, caused by respiration and heartbeat. Due to the superposition of both movements a sophisticated processing of the measured data is necessary to extract the heartbeat and respiration signal from the measured overall signal. This paper presents radar measurements at 24 and 77 GHz, where vital signs of multiple people have been simultaneously monitored and proposes a signal processing method to separate heartbeat and respiration in the measured data.

Number and Angle Analysis in UWB Radar Deployment for Vital Sign Monitoring.

In recent years, more studies focus on the UltraWide Band (UWB) radar to provide a noncontact vital sign monitoring service. To further improve the accuracy of vital sign monitoring, the UWB radar network composed by multiple radars is considered for providing information on different angles. The radar deployment is a key factor in the radar network to impact the monitoring results, since that different deployments bring diverse combinations of vital sign information. To the best of our knowledge, few studies attempt to optimize the radar deployment for the purpose of improving the vital sign monitoring accuracy. This paper provides an analysis on the number and angle in radar deployment for vital sign monitoring. To firstly validate the superiority of utilizing multiple radars rather than the single radar, the theoretical analysis is performed by combining the vital sign monitoring model and the Cramer-Rao Low Bound (CRLB) theory. Then experiments for discussing the effect of the radar number and the angle between radars are conducted in realistic environment. Considering the radar number from 2 to 4, signals are acquired from radars located symmetrically with the subject sitting at the center. Additionally, the deployments of two radars with angles of 0°, 60°, 120°, 180°, 240° and 300° are discussed, ensuring that at least one radar is directed to the chest of the subject. A Neural Network (NN) based data fusion method is performed to obtain the fused vital signal from the radars. The accuracy of the NN is discussed as the evaluating indicators for these deployments.

Noncontact SpO2 Measurement Using Eulerian Video Magnification

Peripheral oxygen saturation (SpO2) monitoring is critical during surgery and in intensive care units (ICS). Over the last decades, several studies have addressed the noncontact monitoring of vital signs, but few reports have focused on SpO2. This paper presents an SpO2 monitoring method without physical contact with the patient using imaging photoplethysmography (iPPG). Eulerian video magnification (EVM) was employed in the proposed solution to amplify the changes in skin color due to the heart cycle. The developed software operates on a widely available, low-cost hardware platform. Experiments were performed with nine healthy individuals. When comparing the experimental SpO2 results to those obtained with a reference pulse oximeter, the proposed solution showed good accuracy, with differences of less than 2%.

Non-Contact, Simple Neonatal Monitoring by Photoplethysmography.

This paper presents non-contact vital sign monitoring in neonates, based on image processing, where a standard color camera captures the plethysmographic signal and the heart and breathing rates are processed and estimated online. It is important that the measurements are taken in a non-invasive manner, which is imperceptible to the patient. Currently, many methods have been proposed for non-contact measurement. However, to the best of the authors’ knowledge, it has not been possible to identify methods with low computational costs and a high tolerance to artifacts. With the aim of improving contactless measurement results, the proposed method based on the computer vision technique is enhanced to overcome the mentioned drawbacks. The camera is attached to an incubator in the Neonatal Intensive Care Unit and a single area in the neonate’s diaphragm is monitored. Several factors are considered in the stages of image acquisition, as well as in the plethysmographic signal formation, pre-filtering and filtering. The pre-filter step uses numerical analysis techniques to reduce the signal offset. The proposed method decouples the breath rate from the frequency of sinus arrhythmia. This separation makes it possible to analyze independently any cardiac and respiratory dysrhythmias. Nine newborns were monitored with our proposed method. A Bland-Altman analysis of the data shows a close correlation of the heart rates measured with the two approaches (correlation coefficient of 0.94 for heart rate (HR) and 0.86 for breath rate (BR)) with an uncertainty of 4.2 bpm for HR and 4.9 for BR (k = 1). The comparison of our method and another non-contact method considered as a standard independent component analysis (ICA) showed lower central processing unit (CPU) usage for our method (75% less CPU usage).

Non-Contact Remote Measurement of Heart Rate Variability using Near-Infrared Photoplethysmography Imaging.

Heart rate variability (HRV) is an important clinical parameter associated with the autonomous nervous system (ANS), age, as well as many diseases such as myocardial infarction, diabetes or renal failure. Gold standard for measurement of HRV is a high-resolution electrocardiogram (ECG). With the current trend towards non-contact and unobtrusive monitoring of vital signs, HRV has also become an interesting and important parameter for non-contact monitoring. In this paper, we present an approach towards non-contact and unobtrusive monitoring of heart rate variability using the camera-based technology of photoplethysmography imaging (PPGI). We investigated the suitability of invisible near-infrared illumination for PPGI, which would enable measurement of HRV in darkness. We compared results obtained using infrared illumination with those obtained using visible light as PPGI illumination and calculated both time-domain as well as frequency-domain HRV parameters. The results achieved with infrared illumination were on par with those using conventional illumination in the visible spectrum. We concluded that infrared illumination enables unobtrusive and non-contact remote HRV measurement in both darkness as well as regular daylight conditions using PPGI.

A Direct Phase-Tracking Doppler Radar Using Wavelet Independent Component Analysis for Non-Contact Respiratory and Heart Rate Monitoring.

A continuous wave Doppler radar, operating as a phase-locked-loop in phase demodulator configuration, is proposed and in vivo demonstrated for noncontact vital signs monitoring. The radar architecture exhibits a unique precision in tracking the phase modulation caused by human cardiopulmonary activity from which heartbeat and respiration can simultaneously be extracted. The single mixer architecture is immune to the null point and does not require small-angle approximation conditions, which distinguishes it from pre-existing other approaches. This enables the proposed radar to behave highly linear, with very precise detection of phase modulations induced by any kind of movement, independently from amplitude and speed. After simulations and technical tests to validate functionality and safety of the proposed architecture, a practical setup was demonstrated on human volunteers. Wavelet independent component analysis was applied to successfully retrieve respiratory and heart rate information from the radar baseband signal.

Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design.

It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is sleeping without hectic movements nearby.

Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz.

Doppler-based non-contact vital signs (NCVS) sensors can monitor heart rates, respiration rates, and motions of patients without physically touching them. We have developed a novel single-board Doppler-based phased-array antenna NCVS biosensor system that can perform robust overnight continuous NCVS monitoring with intelligent automatic subject tracking and optimal beam steering algorithms. Our NCVS sensor achieved overnight continuous vital signs monitoring with an impressive heart-rate monitoring accuracy of over 94% (i.e., within ±5 Beats-Per-Minute vs. a reference sensor), analyzed from over 400,000 data points collected during each overnight monitoring period of ~ 6 hours at a distance of 1.75 meters. The data suggests our intelligent phased-array NCVS sensor can be very attractive for continuous monitoring of low-acuity patients.

Phase-Based Methods for Heart Rate Detection Using UWB Impulse Doppler Radar

Ultra-wideband (UWB) pulse Doppler radars can be used for noncontact vital signs monitoring of more than one subject. However, their detected signals typically have low signal-to-noise ratio (SNR) causing significant heart rate (HR) detection errors, as the spurious harmonics of respiration signals and mixed products of respiration and heartbeat signals (that can be relatively higher than heartbeat signals) corrupt conventional fast Fourier transform spectrograms. In this paper, we extend the complex signal demodulation (CSD) and arctangent demodulation (AD) techniques previously used for accurately detecting the phase variations of reflected signals of continuous wave radars to UWB pulse radars as well. These detection techniques reduce the impact of the interfering harmonic signals, thus improving the SNR of the detected vital sign signals. To further enhance the accuracy of the HR estimation, a recently developed state-space method has been successfully combined with CSD and AD techniques and over 10 dB improvements in SNR is demonstrated. The implementation of these various detection techniques has been experimentally investigated and full error and SNR analysis of the HR detection are presented.

A Review on the Design of Non-Contact Vital Signs (NCVS) Biosensors for Long-Term Continuous Monitoring

It has been the dream of many scientists and engineers to realize a non-contact remote biosensing system that can perform continuous, accurate, and long-term monitoring of human vital signs as what we saw in some SciFi movies. Having a system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a system would also be an effective tool to help physicians and patients make better informed decisions when viewing a patient’s long-term monitored data. Therefore, there has been a large increase in research activities to develop a system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Radio-Frequency (RF) Non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor contact-based sensors for the subjects to worry about. Approach: In this paper, we will provide a brief review on some latest development on NCVS sensors, and also compare them against a novel phased-array Doppler-based RF non-contact NCVS biosensor system we have built in our RF-SoC Lab. To determine the accuracy of our NCVS sensor, the heart rate measurements from our NCVS system are compared against an external contact-based piezoelectric finger sensor as a reference. Objective: In some of our previous works, the NCVS sensor performance was tested within a clutter-free anechoic chamber inside our Lab to mitigate the environmental clutters. To examine the performance of our NCVS sensor in a more practical setting, most tests here were performed within the typical Herman-Miller type office cubicle setting, inside a section of our Lab. Additionally, we will detail the measurement data to demonstrate the feasibility of long-term noncontact vital signs monitoring. Conclusion: The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring, especially for situations where the subject is sleeping and there is not expected to have hectic movements nearby. Recommendation: Our phased-array NCVS biosensor system appears to be quite robust and attractive. We will be performing several 24-hours tests to quantitatively analyze the effects of the background noise to long-term vital signs monitoring in office cubicle setting, and report our findings on these important topics in the near future. In the future, we also plan to continue to perform long-term NCVS monitoring on subjects during their sleep next for potential applications on sleep apnea and sudden cardiac arrest (SCA) patients.

DistancePPG: Robust non-contact vital signs monitoring using a camera.

Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health tracking (e.g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios.

A compact and hand-held infection-screening system for use in rapid medical inspection at airport quarantine stations: system design and preliminary validation

To conduct mass screening and thereby reduce the spread of infection, a compact (13.5 cm × 8.5 cm × 2.5 cm), highly-mobile and hand-held infection-screening system was developed for rapid medical inspection in mass gathering places such as airports. The system is capable of non-contact vital-sign monitoring using two integrated sensors: a 24-GHz microwave radar for measuring heart and respiration rates and a thermopile array for capturing facial temperature. Subsequently, the system detects infected individuals using a linear discriminant function (LDA) from the derived vital-signs data. The system was tested on 10 subjects under two conditions (resting as normal and exercising as pseudo-infected, i.e. a 10-min bicycle ergometer at 100 W exercise); the normal and pseudo-infected conditions were classified successfully via LDA for all subjects (p < 0.01; classification error rate < 5%). The proposed non-contact system can be applied for preventing secondary exposure of medical doctors at the outbreak of highly pathogenic infectious diseases such as the Ebola virus.

2つのマイクロ波レーダーを用いた就寝時高齢者見守りシステム—呼吸・心拍の非接触計測における体動対策—

2つのマイクロ波レーダーを用いた就寝時高齢者見守りシステム—呼吸・心拍の非接触計測における体動対策—

Vital-CUBE: A Non-Contact Vital Sign Monitoring System Using Medical Radar for Ubiquitous Home Healthcare

Vital-CUBE: A Non-Contact Vital Sign Monitoring System Using Medical Radar for Ubiquitous Home Healthcare

Continuous non-contact vital sign monitoring in neonatal intensive care unit.

Current technologies to allow continuous monitoring of vital signs in pre-term infants in the hospital require adhesive electrodes or sensors to be in direct contact with the patient. These can cause stress, pain, and also damage the fragile skin of the infants. It has been established previously that the colour and volume changes in superficial blood vessels during the cardiac cycle can be measured using a digital video camera and ambient light, making it possible to obtain estimates of heart rate or breathing rate. Most of the papers in the literature on non-contact vital sign monitoring report results on adult healthy human volunteers in controlled environments for short periods of time. The authors' current clinical study involves the continuous monitoring of pre-term infants, for at least four consecutive days each, in the high-dependency care area of the Neonatal Intensive Care Unit (NICU) at the John Radcliffe Hospital in Oxford. The authors have further developed their video-based, non-contact monitoring methods to obtain continuous estimates of heart rate, respiratory rate and oxygen saturation for infants nursed in incubators. In this Letter, it is shown that continuous estimates of these three parameters can be computed with an accuracy which is clinically useful. During stable sections with minimal infant motion, the mean absolute error between the camera-derived estimates of heart rate and the reference value derived from the ECG is similar to the mean absolute error between the ECG-derived value and the heart rate value from a pulse oximeter. Continuous non-contact vital sign monitoring in the NICU using ambient light is feasible, and the authors have shown that clinically important events such as a bradycardia accompanied by a major desaturation can be identified with their algorithms for processing the video signal.