SoC CMOS UWB Pulse Radar Sensor for Contactless Respiratory Rate Monitoring

Unobtrusive Sensors for Synchronous Monitoring of Different Breathing Parameters in Care Environments

Respiratory problems are common amongst older people. The rapid increase in the ageing population has led to a need for developing technologies that can monitor such conditions unobtrusively. This paper presents a novel study that investigates Wi-Fi and ultra-wideband (UWB) antenna sensors to simultaneously monitor two different breathing parameters: respiratory rate, and exhaled breath. Experiments were carried out with two subjects undergoing three breathing cases in breaths per minute (BPM): (1) slow breathing (12 BPM), (2) moderate breathing (20 BPM), and (3) fast breathing (28 BPM). Respiratory rates were captured by Wi-Fi sensors, and the data were processed to extract the respiration rates and compared with a metronome that controlled the subjects' breathing. On the other hand, exhaled breath data were captured by a UWB antenna using a vector network analyser (VNA). Corresponding reflection coefficient data (S11) were obtained from the subjects at the time of exhalation and compared with S11 in free space. The exhaled breath data from the UWB antenna were compared with relative humidity, which was measured with a digital psychrometer during the breathing exercises to determine whether a correlation existed between the exhaled breath's water vapour content and recorded S11 data. Finally, captured respiratory rate and exhaled breath data from the antenna sensors were compared to determine whether a correlation existed between the two parameters. The results showed that the antenna sensors were capable of capturing both parameters simultaneously. However, it was found that the two parameters were uncorrelated and independent of one another.

Accurate Contactless Sleep Apnea Detection Framework with Signal Processing and Machine Learning Methods

The detection of sleep apnea is critical for assessing sleep quality. It is also a proven biometric in diagnosing cardiovascular and other diseases. Recent studies have shown that radar-based non-contact vital sign monitoring system can effectively detect sleep apnea. However, the detection accuracy in the current study still needs to be improved. In this paper, we propose a sleep apnea detection framework based on FMCW radar. First, the radar system is employed to record the sleep data throughout the night with polysomnography (PSG) comparison. Then, in order to extract more accurate respiratory signal from the raw radar data, the signal processing methods are investigated to solve the observed discontinuity phenomenon. Finally, machine learning methods are adopted. The apneic and not-apneic events are classified accurately by selecting effective features of respiratory signal. As shown in the experimental results, the proposed system could achieve a good classification performance with an accuracy of 95.53%, a sensitivity of 72.60%, a specificity of 97.32%, a Kappa of 0.68, and an F-score of 0.84.

Experimental demonstration of noncontact vital-sign measurement using pulse radar

BACKGROUD: Recently, monitoring the vital-sign with the noncontact method is a popular technology. OBJECTIVE: In this work, we present a fully pulse radar system including front-end sensing and back-end data processing. A series of ultra-wide band sensing pulses is generated and radiated to detect the subject’s chest vibration which in turn obtains the required vital-sign signals. METHODS: An artificial plywood with 3 centimeter thickness is placed between a transmitting/receiving antenna of the radar and subject to demonstrate the characteristic of noncontact sensing. The firmware and digital signal processing are also presented in this paper to optimize physiological data quality. RESULTS: The experimental results show that the continuous heart rate and breathing rate can be monitored by this customized system radar module. CONCLUSION: A fully customized ultra-wide band radar for vital-sign application is presented. The radar system plan with wall parameter is also incorporated into the design consideration to meet the FCC requirement and SNR.

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

The identification of weak vital signs has always been one of the difficulties in the field of life detection. In this paper, a novel vital sign detection and extraction method with high efficiency, high precision, high sensitivity and high signal-to-noise ratio is proposed. Based on the NVA6100 pulse radar system, the radar matrix which contains several radar pulse detection signals is received. According to the characteristics of vital signs and radar matrices, the Singular Value Decomposition (SVD) is adopted to perform signal denoising and decomposition after preprocessing, and the temporal and spatial eigenvectors of each principal component are obtained. Through the energy proportion screening, the Wavelet Transform decomposition and linear trend suppression, relatively pure vital signs in each principal component, are obtained. The human location is detected by the Energy Entropy of spatial eigenvectors, and the respiratory signal and heartbeat signal are restored through a Butterworth Filter and an MTI harmonic canceller. Finally, through an analysis of the performance of the algorithm, it is proved to have the properties of efficiency and accuracy.

Application of Compressed Sensing 3D MR cholangiopancreatography (CS-MRCP) with Contact-Free Physiological Monitoring (CFPM) for Pancreaticobiliary Disorders

RATIONAL AND OBJECTIVES

To prospectively evaluate the clinical feasibility of the magnetic resonance cholangiopancreatography (MRCP) protocol using both contact-free physiological monitoring (CFPM) and compressed sensing (CS) (CS-CFPM-MRCP) and to compare its performance with that of the standard navigator-triggered (NT) CS-NT-MRCP and NT-MRCP.

MATERIALS AND METHODS

A total of 63 patients (36 males, 27 females, age range: 18-83 years, mean age: 52.30 ± 15.70 years) suspected with duct-related pathologies were prospectively enrolled and performed the three MRCP protocols randomly. The acquisition time was compared. The pancreaticobiliary system was divided into 12 segments and evaluated based on a five-point Likert scale and compared by the Friedman test with a post hoc test. The diagnostic performance of the 3 MRCP was evaluated by the AUC value and compared by Delong's test. The interobserver agreement was evaluated by Kendall's W test.

RESULTS

Compared to NT-MRCP, the acquisition time of CS-NT-MRCP and CS-CFPM-MRCP was significantly decreased (both p < 0.001). There is no significant difference in the overall imaging quality (p > 0.05) between the NT-MRCP and CS-CFPM-MRCP protocols. CS-CFPM-MRCP depicted pancreatic duct and intrahepatic ducts better than CS-NT-MRCP (all p < 0.05) and was comparable with that of the NT-MRCP (all p > 0.05). For identification of abnormalities and diseases associated with MPD anatomy, the mean AUC value for NT-MRCP and CS-CFPM-MRCP were 0.896 (95%CI: 0.834, 0.958) and 0.905 (95%CI: 0.846, 0.964), which were significantly higher when compared to that for CS-NT-MRCP (0.713 [95%CI:0.622, 0.805]) (p = 0.001 and < 0.001). All evaluations showed good to excellent agreement (0.619-0.897).

CONCLUSION

The combination of CS and CFPM is considered feasible for shortening the scan time of 3D free breath MRCP without impairing the imaging quality and CS-CFPM-MRCP is considered feasible for patients suspected with pancreaticobiliary diseases.

Contact and Remote Breathing Rate Monitoring Techniques: A Review

Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients' comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared.

Validation of a New Contactless and Continuous Respiratory Rate Monitoring Device Based on Ultra-Wideband Radar Technology

Respiratory rate (RR) is typically the first vital sign to change when a patient decompensates. Despite this, RR is often monitored infrequently and inaccurately. The Circadia Contactless Breathing Monitor™ (model C100) is a novel device that uses ultra-wideband radar to monitor RR continuously and un-obtrusively. Performance of the Circadia Monitor was assessed by direct comparison to manually scored reference data. Data were collected across a range of clinical and non-clinical settings, considering a broad range of user characteristics and use cases, in a total of 50 subjects. Bland-Altman analysis showed high agreement with the gold standard reference for all study data, and agreement fell within the predefined acceptance criteria of ±5 breaths per minute (BrPM). The 95% limits of agreement were -3.0 to 1.3 BrPM for a nonprobability sample of subjects while awake, -2.3 to 1.7 BrPM for a clinical sample of subjects while asleep, and -1.2 to 0.7 BrPM for a sample of healthy subjects while asleep. Accuracy rate, using an error margin of ±2 BrPM, was found to be 90% or higher. Results demonstrate that the Circadia Monitor can effectively and efficiently be used for accurate spot measurements and continuous bedside monitoring of RR in low acuity settings, such as the nursing home or hospital ward, or for remote patient monitoring.

A Noninvasive Miniaturized Transcutaneous Oxygen Monitor

Transcutaneous monitoring is a noninvasive method to continuously measure the partial pressures of oxygen and carbon dioxide that diffuse through the skin and correlate closely with changes in blood gases. However, the contemporary commercially available electrochemical-based technology requires a heating mechanism and a bulky, corded, and expensive sensing unit. This study aims to demonstrate a prototype noninvasive, miniaturized monitor that uses luminescence-based technology to measure the partial pressure of transcutaneous oxygen, a surrogate of the partial pressure of arterial oxygen. To be able to build a robust measurement system, we conducted experiments to understand the temperature and humidity dependence of oxygen-sensitive platinum-porphyrin films. We performed a detailed analysis of both intensity and lifetime measurement techniques. To verify the performance, we tested the prototype in a small ex-vivo experiment involving three healthy human volunteers. We measured variations in the partial pressure of transcutaneous oxygen values due to pressure-induced arterial and venous occlusions on the volunteers' fingertips. The system resolves changes in the partial pressure of oxygen from 0 to 418 mmHg in the lab bench-top testing, covering the medically relevant range of 50-150 mmHg. Under fixed humidity, temperature, and the partial pressure of oxygen conditions, the sensor shows a 2% drift over 60 hours. The prototype consumes 9 mW of power from a 2.2 V external DC power supply.

Non-Contact Monitoring and Classification of Breathing Pattern for the Supervision of People Infected by COVID-19

During the pandemic of coronavirus disease-2019 (COVID-19), medical practitioners need non-contact devices to reduce the risk of spreading the virus. People with COVID-19 usually experience fever and have difficulty breathing. Unsupervised care to patients with respiratory problems will be the main reason for the rising death rate. Periodic linearly increasing frequency chirp, known as frequency-modulated continuous wave (FMCW), is one of the radar technologies with a low-power operation and high-resolution detection which can detect any tiny movement. In this study, we use FMCW to develop a non-contact medical device that monitors and classifies the breathing pattern in real time. Patients with a breathing disorder have an unusual breathing characteristic that cannot be represented using the breathing rate. Thus, we created an Xtreme Gradient Boosting (XGBoost) classification model and adopted Mel-frequency cepstral coefficient (MFCC) feature extraction to classify the breathing pattern behavior. XGBoost is an ensemble machine-learning technique with a fast execution time and good scalability for predictions. In this study, MFCC feature extraction assists machine learning in extracting the features of the breathing signal. Based on the results, the system obtained an acceptable accuracy. Thus, our proposed system could potentially be used to detect and monitor the presence of respiratory problems in patients with COVID-19, asthma, etc.

Feasibility of non-contact cardiorespiratory monitoring using impulse-radio ultra-wideband radar in the neonatal intensive care unit

Background

Current cardiorespiratory monitoring equipment can cause injuries and infections in neonates with fragile skin. Impulse-radio ultra-wideband (IR-UWB) radar was recently demonstrated to be an effective contactless vital sign monitor in adults. The purpose of this study was to assess heart rates (HRs) and respiratory rates (RRs) in the neonatal intensive care unit (NICU) using IR-UWB radar and to evaluate its accuracy and reliability compared to conventional electrocardiography (ECG)/impedance pneumography (IPG).

Methods

The HR and RR were recorded in 34 neonates between 3 and 72 days of age during minimal movement (51 measurements in total) using IR-UWB radar (HR_Rd, RR_Rd) and ECG/IPG (HR_ECG, RR_IPG) simultaneously. The radar signals were processed in real time using algorithms for neonates. Radar and ECG/IPG measurements were compared using concordance correlation coefficients (CCCs) and Bland-Altman plots.

Results

From the 34 neonates, 12,530 HR samples and 3,504 RR samples were measured. Both the HR and RR measured using the two methods were highly concordant when the neonates had minimal movements (CCC = 0.95 between the RR_Rd and RR_IPG, CCC = 0.97 between the HR_Rd and HR_ECG). In the Bland-Altman plot, the mean biases were 0.17 breaths/min (95% limit of agreement [LOA] -7.0–7.3) between the RR_Rd and RR_IPG and -0.23 bpm (95% LOA -5.3–4.8) between the HR_Rd and HR_ECG. Moreover, the agreement for the HR and RR measurements between the two modalities was consistently high regardless of neonate weight.

Conclusions

A cardiorespiratory monitor using IR-UWB radar may provide accurate non-contact HR and RR estimates without wires and electrodes for neonates in the NICU.

The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise

Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.

Respiratory Monitoring: Current State of the Art and Future Roads

In this article, we present current methodologies, available technologies, and demands for monitoring various respiratory parameters. We discuss the importance of noninvasive techniques for remote and continuous monitoring and challenges involved in the current "smart and connected health" era. We conducted an extensive literature review on the medical significance of monitoring respiratory vital parameters, along with the current methods and solutions with their respective advantages and disadvantages. We discuss the challenges of developing a noninvasive, wearable, wireless system that continuously monitors respiration parameters and opportunities in the field and then determines the requirements of a state-of-the-art system. Noninvasive techniques provide a significant amount of medical information for a continuous patient monitoring system. Contact methods offer more advantages than non-contact methods; however, reducing the size and power of contact methods is critical for enabling a wearable, wireless medical monitoring system. Continuous and accurate remote monitoring, along with other physiological data, can help caregivers improve the quality of care and allow patients greater freedom outside the hospital. Such monitoring systems could lead to highly tailored treatment plans, shorten patient stays at medical facilities, and reduce the cost of treatment.

A UHF/UWB Hybrid RFID Tag With a 51-m Energy-Harvesting Sensitivity for Remote Vital-Sign Monitoring

A novel ultra-high frequency (UHF)/ultra-wideband (UWB) hybrid RFID tag is reported for object-specific remote vital-sign monitoring application. The tag achieves a record energy-harvesting sensitivity at UHF band by codesigning a meander dipole antenna and a passive rectifier. The especially high quality-factor makes the frontend sensitive to near-field motions such as heartbeats and respiration in a wearable setting. The custom CMOS IC of approximately 1-μW power consumption builds around a low-power UWB transmitter and converts variations of the supply voltage to the impulse repetition rate. The tag consisting of the IC and UHF/UWB antennas requires no other discrete components and features a size of 4.2 cm × 2.9 cm and a weight of 0.93 g. A long-distance experiment verifies that the tag can be wirelessly powered up at 51 meters from a 4-W equivalent-isotropic-radiation-power (EIRP) UHF transmitter. Remote vital-sign monitoring is validated on a human subject, in which the UHF power source is placed 2 meters away from the subject with a power emission of less than 20 dBm. This work proposes a first-of-its-kind remote vital-sign monitoring scheme based on a noncontact wearable tag. The design of the far-field energy-harvesting frontend with a record sensitivity serves as a reference for future works on battery-free remote sensors.

Review on Biomedical Sensors, Technologies and Algorithms for Diagnosis of Sleep Disordered Breathing: Comprehensive Survey

This paper provides a comprehensive review of available technologies for measurements of vital physiology related parameters that cause sleep disordered breathing (SDB). SDB is a chronic disease that may lead to several health problems and increase the risk of high blood pressure and even heart attack. Therefore, the diagnosis of SDB at an early stage is very important. The essential primary step before diagnosis is measurement. Vital health parameters related to SBD might be measured through invasive or non-invasive methods. Nowadays, with respect to increase in aging population, improvement in home health management systems is needed more than even a decade ago. Moreover, traditional health parameter measurement techniques such as polysomnography are not comfortable and introduce additional costs to the consumers. Therefore, in modern advanced self-health management devices, electronics and communication science are combined to provide appliances that can be used for SDB diagnosis, by monitoring a patient's physiological parameters with more comfort and accuracy. Additionally, development in machine learning algorithms provides accurate methods of analysing measured signals. This paper provides a comprehensive review of measurement approaches, data transmission, and communication networks, alongside machine learning algorithms for sleep stage classification, to diagnose SDB.

Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review

This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.

Sensing Systems for Respiration Monitoring: A Technical Systematic Review

Respiratory monitoring is essential in sleep studies, sport training, patient monitoring, or health at work, among other applications. This paper presents a comprehensive systematic review of respiration sensing systems. After several systematic searches in scientific repositories, the 198 most relevant papers in this field were analyzed in detail. Different items were examined: sensing technique and sensor, respiration parameter, sensor location and size, general system setup, communication protocol, processing station, energy autonomy and power consumption, sensor validation, processing algorithm, performance evaluation, and analysis software. As a result, several trends and the remaining research challenges of respiration sensors were identified. Long-term evaluations and usability tests should be performed. Researchers designed custom experiments to validate the sensing systems, making it difficult to compare results. Therefore, another challenge is to have a common validation framework to fairly compare sensor performance. The implementation of energy-saving strategies, the incorporation of energy harvesting techniques, the calculation of volume parameters of breathing, or the effective integration of respiration sensors into clothing are other remaining research efforts. Addressing these and other challenges outlined in the paper is a required step to obtain a feasible, robust, affordable, and unobtrusive respiration sensing system.

Recent Advances in ASIC Development for Enhanced Performance M-Sequence UWB Systems

Short-range ultra-wideband (UWB) radar sensors belong to very promising sensing techniques that have received vast attention recently. The M-sequence UWB sensing techniques for radio detection and ranging feature several advantages over the other short-range radars, inter alia superior integration capabilities. The prerequisite to investigate their capabilities in real scenarios is the existence of physically available hardware, i.e., particular functional system blocks. In this paper, we present three novel blocks of M-sequence UWB radars exploiting application-specific integrated circuit (ASIC) technology. These are the integrated 15th-order M-sequence radar transceiver on one chip, experimental active Electronic Communication Committee (ECC) bandpass filter, and miniature transmitting UWB antenna with an integrated amplifier. All these are custom designs intended for the enhancement of capabilities of an M-sequence-based system family for new UWB short-range sensing applications. The design approaches and verification of the manufactured prototypes by measurements of the realized circuits are presented in this paper. The fine balance on technology capabilities (Fc of roughly 120 GHz) and thoughtful design process of the proposed blocks is the first step toward remarkably minimized devices, e.g., as System on Chip designs, which apparently allow broadening the range of new applications.

Wearable radio-frequency sensing of respiratory rate, respiratory volume, and heart rate

Many health diagnostic systems demand noninvasive sensing of respiratory rate, respiratory volume, and heart rate with high user comfort. Previous methods often require multiple sensors, including skin-touch electrodes, tension belts, or nearby off-the-body readers, and hence are uncomfortable or inconvenient. This paper presents an over-clothing wearable radio-frequency sensor study, conducted on 20 healthy participants (14 females) performing voluntary breathing exercises in various postures. Two prototype sensors were placed on the participants, one close to the heart and the other below the xiphoid process to couple to the motion from heart, lungs and diaphragm, by the near-field coherent sensing principle. We can achieve a satisfactory correlation of our sensor with the reference devices for the three vital signs: heart rate (r = 0.95), respiratory rate (r = 0.93) and respiratory volume (r = 0.84). We also detected voluntary breath-hold periods with an accuracy of 96%. Further, the participants performed a breathing exercise by contracting abdomen inwards while holding breath, leading to paradoxical outward thorax motion under the isovolumetric condition, which was detected with an accuracy of 83%.

An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver

Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR- UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate’s health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.

Investigation of an Ultra Wideband Noise Sensor for Health Monitoring

Quick on-scene assessment and early intervention is the key to reduce the mortality of stroke and trauma patients, and it is highly desirable to develop ambulance-based diagnostic and monitoring devices in order to provide additional support to the medical personnel. We developed a compact and low cost ultra wideband noise sensor for medical diagnostics and vital sign monitoring in pre-hospital settings. In this work, we demonstrated the functionality of the sensor for respiration and heartbeat monitoring. In the test, metronome was used to manipulate the breathing pattern and the heartbeat rate reference was obtained with a commercial electrocardiogram (ECG) device. With seventeen tests performed for respiration rate detection, sixteen of them were successfully detected. The results also show that it is possible to detect the heartbeat rate accurately with the developed sensor.

Review-Microwave Radar Sensing Systems for Search and Rescue Purposes

This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor is a non-invasive technique. Recently, many hardware structures, signal processing approaches, and integrated systems have been introduced by researchers in this field. The purpose is to enhance the accuracy of vital signs' detection and location detection and reduce energy consumption. This work concentrates on the representative research on sensing systems that can find alive people under rubble when an earthquake or other disasters occur. In this paper, various operating principles and system architectures for finding survivors using the microwave radar sensors are reviewed. A comparison between these systems is also discussed.

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.

Probabilities of False Alarm for Vital Sign Detection on the Basis of a Doppler Radar System

Vital detection on the basis of Doppler radars has drawn a great deal of attention from researchers because of its high potential for applications in biomedicine, surveillance, and finding people alive under debris during natural hazards. In this research, the signal-to-noise ratio (SNR) of the remote vital-sign detection system is investigated. On the basis of different types of noise, such as phase noise, Gaussian noise, leakage noise between the transmitting and receiving antennae, and so on, the SNR of the system has first been examined. Then the research has focused on the investigation of the detection and false alarm probabilities of the system when the transmission link between the human and the radar sensor system took the Nakagami-m channel model. The analytical model for the false alarm and the detection probabilities of the system have been derived. The proposed theoretical models for the SNR and detection probability match with the simulation and measurement results. These theoretical models have the potential to be used as good references for the hardware development of the vital-sign detection radar sensor system.

A 24-GHz Front-End Integrated on a Multilayer Cellulose-Based Substrate for Doppler Radar Sensors

This paper presents a miniaturized Doppler radar that can be used as a motion sensor for low-cost Internet of things (IoT) applications. For the first time, a radar front-end and its antenna are integrated on a multilayer cellulose-based substrate, built-up by alternating paper, glue and metal layers. The circuit exploits a distributed microstrip structure that is realized using a copper adhesive laminate, so as to obtain a low-loss conductor. The radar operates at 24 GHz and transmits 5 mW of power. The antenna has a gain of 7.4 dBi and features a half power beam-width of 48 degrees. The sensor, that is just the size of a stamp, is able to detect the movement of a walking person up to 10 m in distance, while a minimum speed of 50 mm/s up to 3 m is clearly measured. Beyond this specific result, the present paper demonstrates that the attractive features of cellulose, including ultra-low cost and eco-friendliness (i.e., recyclability and biodegradability), can even be exploited for the realization of future high-frequency hardware. This opens opens the door to the implementation on cellulose of devices and systems which make up the "sensing layer" at the base of the IoT ecosystem.

A Detailed Algorithm for Vital Sign Monitoring of a Stationary/Non-Stationary Human through IR-UWB Radar

The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient's respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing and heart rate frequencies are extracted from the signal reflected from the human body. A Kalman filter is applied to reduce the measurement noise from the vital signal. An algorithm is presented to separate the heart rate signal from the breathing harmonics. An auto-correlation based technique is applied for detecting random body movements (RBM) during the measurement process. Experiments were performed in different scenarios in order to show the validity of the algorithm. The vital signs were estimated for the signal reflected from the chest, as well as from the back side of the body in different experiments. The results from both scenarios are compared for respiration and heartbeat estimation accuracy.

SleepSense: A Noncontact and Cost-Effective Sleep Monitoring System

Quality of sleep is an important indicator of health and well being. Recent developments in the field of in-home sleep monitoring have the potential to enhance a person's sleeping experience and contribute to an overall sense of well being. Existing in-home sleep monitoring devices either fail to provide adequate sleep information or are obtrusive to use. To overcome these obstacles, a noncontact and cost-effective sleep monitoring system, named SleepSense, is proposed for continuous recognition of the sleep status, including on-bed movement, bed exit, and breathing section. SleepSense consists of three parts: a Doppler radar-based sensor, a robust automated radar demodulation module, and a sleep status recognition framework. Herein, several time-domain and frequency-domain features are extracted for the sleep recognition framework. A prototype of SleepSense is presented and evaluated using two sets of experiments. In the short-term controlled experiment, the SleepSense achieves an overall 95.1% accuracy rate in identifying various sleep status. In the 75-minute sleep study, SleepSense demonstrates wide usability in real life. The error rate for breathing rate extraction in this study is only 6.65%. These experimental results indicate that SleepSense is an effective and promising solution for in-home sleep monitoring.

The Internet of Things for basic nursing care-A scoping review

BACKGROUND

The novel technology of the Internet of Things (IoT) connects objects to the Internet and its most advanced applications refine obtained data for the user. We propose that Internet of Things technology can be used to promote basic nursing care in the hospital environment by improving the quality of care and patient safety.

OBJECTIVES

To introduce the concept of Internet of Things to nursing audience by exploring the state of the art of Internet of Things based technology for basic nursing care in the hospital environment.

DATA SOURCES AND REVIEW METHODS

Scoping review methodology following Arksey & O'Malley's stages from one to five were used to explore the extent, range, and nature of current literature. We searched eight databases using predefined search terms. A total of 5030 retrievals were found which were screened for duplications and relevancy to the study topic. 265 papers were chosen for closer screening of the abstracts and 93 for full text evaluation. 62 papers were selected for the review. The constructs of the papers, the Internet of Things based innovations and the themes of basic nursing care in hospital environment were identified.

RESULTS

Most of the papers included in the review were peer-reviewed proceedings of technological conferences or articles published in technological journals. The Internet of Things based innovations were presented in methodology papers or tested in case studies and usability assessments. Innovations were identified in several topics in four basic nursing care activities: comprehensive assessment, periodical clinical reassessment, activities of daily living and care management.

CONCLUSIONS

Internet of Things technology is providing innovations for the use of basic nursing care although the innovations are emerging and still in early stages. Internet of things is yet vaguely adopted in nursing. The possibilities of the Internet of Things are not yet exploited as well as they could. Nursing science might benefit from deeper involvement in engineering research in the area of health.

On the Use of Knitted Antennas and Inductively Coupled RFID Tags for Wearable Applications

Recent advancements in conductive yarns and fabrication technologies offer exciting opportunities to design and knit seamless garments equipped with sensors for biomedical applications. In this paper, we discuss the design and application of a wearable strain sensor, which can be used for biomedical monitoring such as contraction, respiration, or limb movements. The system takes advantage of the intensity variations of the backscattered power (RSSI) from an inductively-coupled RFID tag under physical stretching. First, we describe the antenna design along with the modeling of the sheet impedance, which characterizes the conductive textile. Experimental results with custom fabricated prototypes showed good agreement with the numerical simulation of input impedance and radiation pattern. Finally, the wearable sensor has been applied for infant breathing monitoring using a medical programmable mannequin. A machine learning technique has been developed and applied to post-process the RSSI data, and the results show that breathing and non-breathing patterns can be successfully classified.

Short-Range Vital Signs Sensing Based on EEMD and CWT Using IR-UWB Radar

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.

Contactless respiration rate measurement using optical method and empirical mode decomposition

BACKGROUND

At the emergency triage center, assessment of the present of the danger signs and measurement of vital signs are measured according to the guidelines. The respiration rate is still posing a challenge to the doctor as it is impractical to use conventional devices. Attaching measurement devices to the patient will induce artificial measurements (self-awareness stress effects) besides being time-consuming. Currently, the medical officers visually count the number of times the chest movement in a minute, sometimes poses cultural challenges especially for female patients.

OBJECTIVE

The main objective of this paper is to develop a robust algorithm to extract respiration rate using the contactless displacement sensor.

METHODS

In this study, chest movements were used as an indicative of inspiration and expiration to measure respiratory rate using the contactless displacement sensor. The contactless optical signals were recorded from 32 healthy subjects in four different controlled breathing conditions: rest, coughing, talking and hand movement to obtain the motion artifacts that the patients may have in the emergency department. The Empirical mode decomposition (EMD) algorithm was used to derive continuous RR signal from the contactless optical signal.

RESULTS

The analysis showed that there is a good correlation (0.9702) with RMSE of 0.33 breaths per minutes between the contact respiration rate and contactless respiration rate using empirical mode decomposition method.

CONCLUSION

It can be concluded that the empirical mode decomposition method can extract the respiration rate of the contactless optical signal from chest movement.

Contactless respiratory monitoring system for magnetic resonance imaging applications using a laser range sensor

During a magnetic resonance imaging (MRI) exam, a respiratory signal can be required for different purposes, e.g. for patient monitoring, motion compensation or for research studies such as in functional MRI. In addition, respiratory information can be used as a biofeedback for the patient in order to control breath holds or shallow breathing. To reduce patient preparation time or distortions of the MR imaging system, we propose the use of a contactless approach for gathering information about the respiratory activity. An experimental setup based on a commercially available laser range sensor was used to detect respiratory induced motion of the chest or abdomen. This setup was tested using a motion phantom and different human subjects in an MRI scanner. A nasal airflow sensor served as a reference. For both, the phantom as well as the different human subjects, the motion frequency was precisely measured. These results show that a low cost, contactless, laser-based approach can be used to obtain information about the respiratory motion during an MRI exam.

A Self-Calibrating Radar Sensor System for Measuring Vital Signs

Vital signs (i.e., heartbeat and respiration) are crucial physiological signals that are useful in numerous medical applications. The process of measuring these signals should be simple, reliable, and comfortable for patients. In this paper, a noncontact self-calibrating vital signs monitoring system based on the Doppler radar is presented. The system hardware and software were designed with a four-tiered layer structure. To enable accurate vital signs measurement, baseband signals in the radar sensor were modeled and a framework for signal demodulation was proposed. Specifically, a signal model identification method was formulated into a quadratically constrained l1 minimization problem and solved using the upper bound and linear matrix inequality (LMI) relaxations. The performance of the proposed system was comprehensively evaluated using three experimental sets, and the results indicated that this system can be used to effectively measure human vital signs.

A home sleep apnea screening device with time-domain signal processing and autonomous scoring capability

Current solutions of sleep apnea diagnosis require the patient to undergo overnight studies at a specialized sleep laboratory. Due to such inconvenience and high cost, millions of sleep apnea patients remain undiagnosed and thus untreated. Based on a micro-electro-mechanical systems (MEMS) sensor and an effective apnea detection algorithm, we propose a low-cost single-channel apnea screening solution applicable in the comfort of patients' homes. A prototype device was designed and assembled including a MEMS sensor for measuring the patient's nasal air flows, and a time-domain signal processing IC for apnea detection and autonomous scoring. The IC chip was fabricated in standard 0.5- μm CMOS technology. The proposed device was tested for both respiratory rhythm detection and sleep apnea screening under clinical environment. Apnea-hypopnea indices (AHI) were scored to indicate severity of sleep apnea conditions. Test results suggest that the proposed device can be a valuable screening solution for the broader public with undiagnosed apnea conditions.

Respiration detection chip with integrated temperature-insensitive MEMS sensors and CMOS signal processing circuits

An airflow sensing chip, which integrates MEMS sensors with their CMOS signal processing circuits into a single chip, is proposed for respiration detection. Three micro-cantilever-based airflow sensors were designed and fabricated using a 0.35 μm CMOS/MEMS 2P4M mixed-signal polycide process. Two main differences were present among these three designs: they were either metal-covered or metal-free structures, and had either bridge-type or fixed-type reference resistors. The performances of these sensors were measured and compared, including temperature sensitivity and airflow sensitivity. Based on the measured results, the metal-free structure with fixed-type reference resistors is recommended for use, because it has the highest airflow sensitivity and also can effectively reduce the output voltage drift caused by temperature change.

Time-lapse imaging of human heart motion with switched array UWB radar

Radar systems for detection of human heartbeats have mostly been single-channel systems with limited spatial resolution. In this paper, a radar system for ultra-wideband (UWB) imaging of the human heart is presented. To make the radar waves penetrate the human tissue the antenna is placed very close to the body. The antenna is an array with eight elements, and an antenna switch system connects the radar to the individual elements in sequence to form an image. Successive images are used to build up time-lapse movies of the beating heart. Measurements on a human test subject are presented and the heart motion is estimated at different locations inside the body. The movies show rhythmic motion consistent with the beating heart, and the location and shape of the reflections correspond well with the expected response form the heart wall. The spatial dependent heart motion is compared to ECG recordings, and it is confirmed that heartbeat modulations are seen in the radar data. This work shows that radar imaging of the human heart may provide valuable information on the mechanical movement of the heart.

Noncontact proximity vital sign sensor based on PLL for sensitivity enhancement

In this paper, a noncontact proximity vital sign sensor, using a phase locked loop (PLL) incorporated with voltage controlled oscillator (VCO) built-in planar type circular resonator, is proposed to enhance sensitivity in severe environments. The planar type circular resonator acts as a series feedback element of the VCO as well as a near-field receiving antenna. The frequency deviation of the VCO related to the body proximity effect ranges from 0.07 MHz/mm to 1.8 MHz/mm (6.8 mV/mm to 205 mV/mm in sensitivity) up to a distance of 50 mm, while the amount of VCO drift is about 21 MHz in the condition of 60 (°)C temperature range and discrete component tolerance of ± 5%. Total frequency variation occurs in the capture range of the PLL which is 60 MHz. Thus, its loop control voltage converts the amount of frequency deviation into a difference of direct current (DC) voltage, which is utilized to extract vital signs regardless of the ambient temperature. The experimental results reveal that the proposed sensor placed 50 mm away from a subject can reliably detect respiration and heartbeat signals without the ambiguity of harmonic signals caused by respiration signal at an operating frequency of 2.4 GHz.

Techniques for clutter suppression in the presence of body movements during the detection of respiratory activity through UWB radars

This paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some techniques to solve several problems in these types of measurements, such as the clutter suppression, body movement and body orientation detection are described. Clutter suppression is achieved using a moving averaging filter to dynamically estimate it. The artifacts caused by body movements are removed using a threshold method before analyzing the breathing signal. The motion is detected using the time delay that maximizes the received signal after a clutter removing algorithm is applied. The periods in which the standard deviations of the time delay exceed a threshold are considered macro-movements and they are neglected. The sleep apnea intervals are detected when the breathing signal is below a threshold. The breathing rate is determined from the robust spectrum estimation based on Lomb periodogram algorithm. On the other hand the breathing signal amplitude depends on the body orientation respect to the antennas, and this could be a problem. In this case, in order to maximize the signal-to-noise ratio, multiple sensors are proposed to ensure that the backscattered signal can be detected by at least one sensor, regardless of the direction the human subject is facing. The feasibility of the system is compared with signals recorded by a microphone.

Development of unconstrained heartbeat and respiration measurement system with pneumatic flow

The management of health through daily monitoring of heartbeat and respiration signals is of major importance for early diagnosis to prevent diseases of the respiratory and circulatory system. However, such daily health monitoring is possible only if the monitoring system is physically and psychologically noninvasive. In this paper, an unconstrained method of measuring heartbeat and respiration signals, by using a thermistor to measure the air flows from the air mattress to an air tube accompanying the subject's heartbeat and respiration, is proposed. The SN ratio with interference by opening and closing of a door as environmental noise was compared with that obtained by the conventional condenser microphone method. As a result, the SN ratios with the condenser microphone method were 26.6 ± 4.2 dB for heartbeat and 27.8 ± 3.0 dB for respiration, whereas with the proposed method they were 34.9 ± 3.1 dB and 42.1 ± 2.5 dB, respectively.