Non-contact Vital Sign Monitoring Research Articles

Enhancement of Remote Vital Sign Monitoring Detection Accuracy Using Multiple-Input Multiple-Output 77 GHz FMCW Radar

Remote non-contact monitoring of human vital signs has recently received lots of attention due to the advancement and availability of millimeter wave (mmWave) radars. These sensors are significantly reduced in size, but still face serious electromagnetic (EM) propagation loss and signal obstructions resulting in lower signal-to-noise ratios (SNR). As mmWave received signals also have higher sensitivity to body motions, these effects typically degrade the accuracy of heart rate (HR) detection. To overcome this challenge, MIMO configuration can be used to improve the SNR level by taking advantage of its channel diversity. We use here a Frequency Modulated Continuous Wave (FMCW) radar from Texas Instruments (TI) at 77 GHz to collect data from 192 channels. Additionally, vital sign information is extracted using Arctangent Demodulation (AD) and Maximal Ratio Combining (MRC) combined with an adapted-wavelet Continuous Wavelet Transform (CWT) are utilized to demonstrate improvement of HR estimation accuracy.

Noncontact Multi-Target Respiration Sensing Using SIMO Radar With UBSS Method

Effectively extracting vital signs from multiple targets has been challenging for non-contact vital signs monitoring. This letter presents a nonlinear projection-affinity propagation (NP-AP) clustering-based underdetermined blind source separation (UBSS) approach that can isolate respiratory signals of multiple targets in an underdetermined condition without predetermining the number of targets. The proposed algorithm can provide an accurate estimation of the mixing matrix and is robust to the noises. The experimental result with three human subjects demonstrates the effectiveness of the proposed method in a real scenario.

Quadrature Cosine Transform (QCT) With Varying Window Length (VWL) Technique for Noncontact Vital Sign Monitoring Using a Continuous-Wave (CW) Radar

For noncontact vital sign monitoring by using a continuous-wave (CW) radar, the quadrature cosine transform (QCT) with varying window length (VWL) technique is proposed in this article for the first time. The novel algorithm can directly yield the vibration frequency of the radar’s output <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IQ</i> signals with multiple advantages, including the elimination of dc offset calibration and mitigation of nonlinear interferences caused by harmonic and intermodulation terms, and there is a 50% reduction in frequency resolution of the conventional Fourier transform (FT) that is commonly utilized in existing articles. Thus, it can strike a balance between accuracy and computational efficiency with a short window length. The excellent performance was demonstrated by both theoretical predictions and simulation results. Experiments involving a participant seated 1 m away from the 2.4-GHz ISM band radar prototype demonstrated that the proposed algorithm measures the respiratory rate variability (RRV) and short-time heart rate (HR) with respective errors of less than 1% and 3%. Moreover, the proposed algorithm was more accurate than conventional methods with various window lengths (3–27 s) in 10-min noncontact experiments to monitor the vital signs of ten participants.

A medical radar system for non-contact vital sign monitoring and clinical performance evaluation in hospitalized older patients

Medical radar plays an important role in non-contact vital sign monitoring. However, radar is sensitive and susceptible to noise that deteriorates signal quality, making its application unstable in medical practice settings. Previous studies have focused on detecting vital signs from radar output, but mainly used high-quality signals in laboratory settings. Therefore, signal quality evaluation to maintain good-quality signals for processing is crucial for radar applications. This paper presents a vital sign monitoring system using medical radar that automatically evaluates signal quality to eliminate unsatisfactory signals using the support-vector machine and to extract heartbeat and respiration signals using the singular value decomposition method. To evaluate the system performance, we tested it on 10 healthy subjects and compared the obtained vital signs with those measured using a contact-type ECG device and a respiration belt. Two evaluation steps were conducted. First, we measured 10 subjects for evaluating the signal quality in a laboratory setting. The results showed that the accuracy for each subject archive was 93.2%–100%. Second, we extracted vital signs including respiration rate (RR) and the heart rate (HR) following signal quality classification. The results showed RR and HR deviation from 0 to 1 bpm, and 0 to 4 bpm, respectively. Moreover, the system was applied in a real medical practice setting for continuously monitoring the bedside of hospitalized older patients at a hospital.

Remote Vital Signs Measurement of Indoor Walking Persons Using mm-Wave FMCW Radar

Research on radar-based non-contact vital sign monitoring systems is critical during the COVID-19 epidemic. The accuracy of remote vital sign measurements has increased with the advancement of radar technology and various algorithms. Most studies require subjects to remain stationary, such as standing, sitting in a chair, or lying on a bed, and various measurement algorithms have been proposed. However, maintaining a stationary state as a prerequisite for measurement limits the development and application prospects of radar-based vital sign monitoring systems. Therefore, this paper presents a novel method for monitoring the vital signs of moving targets using a millimeter-wave frequency-modulated continuous-wave (FMCW) radar. The experimental results showed that regardless of whether the subjects walked at 1 m/s or with the left side of their body facing the radar, the accuracy of the heart rate measurement remained high. In the fixed-route experiments, the root mean squared error (RMSE) for heart rate estimation was 4.09 bpm, with an accuracy of 95.88%.

VitaSi: A real-time contactless vital signs estimation system

The non-contact monitoring of vital signs, especially the Heart Rate (HR) and Breathing Rate (BR), using facial video is becoming increasingly important. Although, researchers have made considerable progress in the past few years, there are still some limitations to the technology, such as the lack of challenging datasets, the time consuming nature of the estimation process, and non-portability of the system. In this paper, we proposed a new framework for estimating HRs and BRs by combining a Convolutional Neural Network (CNN) with the Phase-based Video Motion Processing (PVMP) algorithm. The experimental results show that our approach achieves better performance. Meanwhile, we introduce a new challenging dataset with fewer constraints, such as large movements, facial expressions and light interference. In addition, we developed a new Android application, which works in real time and offline, based on a CNN for HR and BR estimations.

Continuous Camera-Based Premature-Infant Monitoring Algorithms for NICU

Non-contact visual monitoring of vital signs in neonatology has been demonstrated by several recent studies in ideal scenarios where the baby is calm and there is no medical or parental intervention. Similar to contact monitoring methods (e.g., ECG, pulse oximeter) the camera-based solutions suffer from motion artifacts. Therefore, during care and the infants’ active periods, calculated values typically differ largely from the real ones. In this way, our main contribution to existing remote camera-based techniques is to detect and classify such situations with a high level of confidence. Our algorithms can not only evaluate quiet periods, but can also provide continuous monitoring. Altogether, our proposed algorithms can measure pulse rate, breathing rate, and to recognize situations such as medical intervention or very active subjects using only a single camera, while the system does not exceed the computational capabilities of average CPU-GPU-based hardware. The performance of the algorithms was evaluated on our database collected at the Ist Dept. of Neonatology of Pediatrics, Dept of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary.

Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks.

Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland–Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.

24 GHz Flexible Antenna for Doppler Radar-Based Human Vital Signs Monitoring.

Noncontact monitoring of human vital signs has been an emerging research topic in recent years. A key approach to this monitoring is the use of the Doppler radar concept which enables real-time vital signs detection, resulting in a new class of radar system known as bio-radar. The antennas are a key component of any bio-radar module and their designs should meet the common requirements of bio-radar applications such as high radiation directivity and mechanical flexibility. This paper presents the design of a four-element antenna array on a flexible liquid crystal polymer (LCP) substrate of 100 μm thickness and εr of 3.35. The designed antenna array can be used with a 24 GHz bio-radar for vital signs monitoring in a non-contact manner. It features a relatively compact size of 36.5 × 53 mm2 and measured gain of 5.81 dBi. The two vital signs: breathing rate (BR) and heart rate (HR) of two human subjects are detected with relatively good accuracy using the fabricated antenna array and radio frequency (RF) output power of −3 dBm from a distance of approximately 60 cm. The effect of bending on the antenna performance is also analyzed.

Radar detection of multi-target vital signs based on blind source separation

Radar non-contact monitoring of vital signs has a broad application prospect in clinical monitoring. Aiming at the problem of strong interference in non-contact vital signs detection (Such as multi-target, random body motion), a blind source separation (BSS) signal detection method based on Fast-ICA is proposed to reduce the interference of multi-target. In this algorithm, entropy is used to evaluate the non Gaussian property, and the appropriate transformation matrix is selected, according to the statistical independence of the signals, the source signals are separated from the observed mixed signals. On this basis, the traditional blind source separation process is improved, and the wavelet transform preprocessing algorithm based on translation invariant is added to suppress the interference of static clutter. The feasibility of this method is verified by simulation experiments.

Computer system for metrological testing of location sensors used to monitor the patient's condition in magnetotherapy

Non-contact monitoring of vital signs of a person is a reliable and safe way of promptly obtaining objective diagnostic information about the current physiological state of a patient during surgical operations, physiotherapeutic procedures or during sleep. The absence of direct contact of the sensors with the patient's body makes it possible to exclude the influence of a number of interfering factors, such as a violation or weakening of contact, which can lead to a deterioration in the quality of signals from the output of the sensors, a long-term location of the sensors on the body can have a psychological effect on the patient, changing his condition and thereby distorting the treatment method, etc. In order for the results of monitoring and diagnostics to be reliable and guaranteed accurate, it is necessary to carry out periodic metrological certification of location sensors, especially since many of them are of foreign production and their characteristics are either not standardized or do not meet the requirements of their operating conditions. Therefore, the tasks of developing methods and means for carrying out metrological tests of non-contact sensors for medical purposes are becoming urgent. Purpose – to show the possibility of implementing automated metrological tests of location sensors for medical use based on a personal computer and publicly available standard hardware and software. A method has been developed and implemented for conducting metrological tests of location sensors based on a personal computer, a digital dynamic measure of linear displacement, virtual measuring instruments, laser and ultrasonic sensors, as well as determining conversion errors in the LabVIEW environment. As an exemplary measuring instrument, it is proposed to use a webcam with a virtual device for recording the law of displacement in the LabVIEW Vison Development application. Full-scale experiments have been carried out, in which, using a digital measure of linear displacement, it is possible to reproduce with high accuracy almost any law of displacement and to regulate its informative parameters. Real movement signals were received with the help of virtual devices, recorded by two location sensors and a web camera. The errors of the means of registration are determined in comparison with the given digital method and analytically the law of movement. Introduction of the developed method and hardware and software for metrological certification of sensors of diagnostic channels of the systems of complex magnetotherapy «Multimag» and «Relaxmag». Carrying out automated metrological tests of sensors will ensure prompt, reliable and objective control of their actual characteristics, which means it will increase the effectiveness of treatment due to the prompt and continuous monitoring of the patient's functional state and an objective assessment of a number of important indicators.

Noncontact Vital Sign Monitoring System with Dual Infrared Imaging for Discriminating Respiration Mode

Noncontact Vital Sign Monitoring System with Dual Infrared Imaging for Discriminating Respiration Mode

Multi-Resident Non-Contact Vital Sign Monitoring Using Radar: A Review

Vital signs are inarguably accepted as important key constituents to improve the health condition. Worldwide medical institutions and clinical observations have emphasized the need for continuous monitoring of vital signs such as heart rate (HR) and respiration rate (RR) for better health management. Radars are investigated as one of the potential technologies for non-contact continuous monitoring of vital signs. This paper provides a comprehensive technological review on the current state-of-art of non-contact vital sign (NCVS) measurements using radar. We highlight the need to move towards higher frequency for high accuracy in a multi-resident environment and analyze the implications of mmWave exposure on human health and the effect of environmental attenuation. Significant challenges associated with hardware and signal processing algorithm are discussed in detail. Finally, we conclude the review with future directions and challenges associated with the detection of vital signs in a multi-resident indoor environment.

Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment

A clinical study was designed to record a wide range of physiological values from patients undergoing haemodialysis treatment in the Renal Unit of the Churchill Hospital in Oxford. Video was recorded for a total of 84 dialysis sessions from 40 patients during the course of 1 year, comprising an overall video recording time of approximately 304.1 h. Reference values were provided by two devices in regular clinical use. The mean absolute error between the heart rate estimates from the camera and the average from two reference pulse oximeters (positioned at the finger and earlobe) was 2.8 beats/min for over 65% of the time the patient was stable. The mean absolute error between the respiratory rate estimates from the camera and the reference values (computed from the Electrocardiogram and a thoracic expansion sensor—chest belt) was 2.1 breaths/min for over 69% of the time for which the reference signals were valid. To increase the robustness of the algorithms, novel methods were devised for cancelling out aliased frequency components caused by the artificial light sources in the hospital, using auto-regressive modelling and pole cancellation. Maps of the spatial distribution of heart rate and respiratory rate information were developed from the coefficients of the auto-regressive models. Most of the periods for which the camera could not produce a reliable heart rate estimate lasted under 3 min, thus opening the possibility to monitor heart rate continuously in a clinical environment.

Adaptive Separation of Respiratory and Heartbeat Signals among Multiple People Based on Empirical Wavelet Transform Using UWB Radar

The non-contact monitoring of vital signs by radar has great prospects in clinical monitoring. However, the accuracy of separated respiratory and heartbeat signals has not satisfied the clinical limits of agreement. This paper presents a study for automated separation of respiratory and heartbeat signals based on empirical wavelet transform (EWT) for multiple people. The initial boundary of the EWT was set according to the limited prior information of vital signs. Using the initial boundary, empirical wavelets with a tight frame were constructed to adaptively separate the respiratory signal, the heartbeat signal and interference due to unconscious body movement. To verify the validity of the proposed method, the vital signs of three volunteers were simultaneously measured by a stepped-frequency continuous wave ultra-wideband (UWB) radar and contact physiological sensors. Compared with the vital signs from contact sensors, the proposed method can separate the respiratory and heartbeat signals among multiple people and obtain the precise rate that satisfies clinical monitoring requirements using a UWB radar. The detection errors of respiratory and heartbeat rates by the proposed method were within ±0.3 bpm and ±2 bpm, respectively, which are much smaller than those obtained by the bandpass filtering, empirical mode decomposition (EMD) and wavelet transform (WT) methods. The proposed method is unsupervised and does not require reference signals. Moreover, the proposed method can obtain accurate respiratory and heartbeat signal rates even when the persons unconsciously move their bodies.

Non-contact vital sign monitoring of patients in an intensive care unit: A human factors analysis of staff expectations

BackgroundInfra-red and thermal imaging enable wireless systems to monitor patients’ vital signs and absence of wires may improve patient experiences. No studies have explored staff perceptions of the concept of this specific type of technology in the adult population. Understanding existing working systems before introducing technology could improve adoption. MethodsWe conducted semi-structured interviews with Intensive Care Unit (ICU) staff exploring perceptions of wireless patient monitoring. We used the Systems Engineering Initiative for Patient Safety (SEIPS) model to guide thematic analysis. ResultsWe identified usability themes relating to staff perceptions of current patient monitoring experiences, staff perceptions of patient/relative expectations of ICU care, troubleshooting, hierarchy of monitoring, and consensus of trust. ConclusionThe concept of wireless monitoring has perceived benefits for patients and staff. The Systems Engineering Initiative for Patient Safety model guided a systems-based exploratory evaluation. Results highlight the social and environmental factors which may influence usability, adoption, or abandonment of wireless technology in the ICU.

MMT-HEAR: Multiple Moving Targets Heartbeats Estimation and Recovery Using IR-UWB Radars.

Populations around the world are rapidly ageing. Age-friendly environments address the significance of continuous inhome vital sign monitoring. Impulse Radio Ultra-WideBand (IR-UWB) radar serves as a household healthcare assistance, providing non-contact vital sign monitoring without privacy issues and illumination limitation. However, the body movements bring difficulty in extracting heartbeat from radar signals, let alone obtaining complete information with body occlusions among multiple targets. This paper proposes a Multiple Moving Targets Heartbeat Estimation And Recovery (MMT-HEAR) approach to extract vital signs using IR-UWB radars. CLEAN and Joint Probability Data Association (JPDA) algorithms are firstly performed on each radar to estimate target-to-antenna distances of multiple targets. Considering signal obstruction and attenuation for targets occluded by others, the location-based distance optimization is proposed to refine these distances by combining information from all radars. Then the mapping from signal amplitudes to refined distances is introduced and combined with the Variational Nonlinear Chirp Mode Decomposition (VNCMD) to extract vital signs with body movements. To the best of our knowledge, this is the first attempt to monitor vital signs of multiple moving targets with radars. The averaging accuracy for two moving targets heartbeat monitoring during a 20-minutes observation is 85.93% with MMT-HEAR. Compared to two other conventional methods, the MMT-HEAR approach yields improvements of 16.11% and 10.16%, revealing the efficiency and robustness of this proposed approach.

Small Motion Detection and Non-Contact Vital Signs Monitoring with Continuous Wave Doppler Radars

Radars have become devices that one can come across in any environment at any moment. This means that they enter to all areas of life and even in the field of medicine and will be used more intensively in the future. Especially, the attention has been drawn to that they are suitable for the non-contact vital signs monitoring. In this study, two radar structures operating at 24 GHz (Radar 1) and 2.4 GHz (Radar 2) frequencies are used. Radar 1 structure is created on a printed circuit board (PCB), whereas Radar 2 is obtained by combining discrete components. The 8.5 mm movement performed with the aid of a test mechanism is detected by two radars with percentage errors (PEs) of 2.58% and 6.23%, respectively. For the 0.25 Hz vibration frequency, the error is the same for both radars and is 2.4 %. In measurements taken from a healthy human subject, Radar 1 finds a respiration rate with 1.85 % of PE and heart beat rate with 6.17 % of PE. In Radar 2, these values are 2.35 % and 8.24 %, respectively. From the measurement results, it is seen that the resolution of Radar 1 is better than that of Radar 2. The results also indicate that small motion detection and vital signs monitoring are carried out successfully.

Monitoramento da taxa de saturação de oxigênio no sangue e frequência cardíaca via método de magnificação Euleriana sem contato físico

O monitoramento da frequência cardíaca (FC) e da taxa de saturação de oxigênio no sangue (SpO2) é fundamental em cirurgias e unidades de terapia intensiva. Nas últimas décadas surgiram vários estudos sobre monitoramento de sinais vitais sem contato físico, mas poucos são focados na SpO2. Este artigo apresenta uma solução para o monitoramento da taxa de saturação de oxigênio no sangue e frequência cardíaca sem contato físico com o paciente através da técnica de fotopletismografia por imagens. A magnificação de vídeo Euleriana (EVM) foi empregada na solução proposta para ampliar as variações de cores que ocorrem na pele devido ao ciclo circadiano. O software desenvolvido foi executado em uma plataforma de hardware livre e de baixo custo.Foram realizados experimentos com nove indivíduos saudáveis. Ao comparar os resultados experimentais com os obtidos com um oxímetro de pulso de referência, a solução proposta mostrou boa acurácia nas medidas de SpO2, com diferença menor que 2%, atendendo os requisitos da norma que regulamenta os equipamentos de oximetria de pulso.

Optimal Central Frequency for Non-Contact Vital Sign Detection Using Monocycle UWB Radar.

Ultra-wideband (UWB) radar has become a critical remote-sensing tool for non-contact vital sign detection such as emergency rescues, securities, and biomedicines. Theoretically, the magnitude of the received reflected signal is dependent on the central frequency of mono-pulse waveform used as the transmitted signal. The research is based on the hypothesis that the stronger the received reflected signals, the greater the detectability of life signals. In this paper, we derive a new formula to compute the optimal central frequency to obtain as maximum received reflect signal as possible over the frequency up to the lower range of Ka-band. The proposed formula can be applicable in the optimization of hardware for UWB life detection and non-contact monitoring of vital signs. Furthermore, the vital sign detection results obtained by the UWB radar over a range of central frequency have been compared to those of the former continuous (CW) radar to provide additional information regarding the advantages and disadvantages of each radar.