An X-band microwave life-detection system

Model-based estimation of heart movements using microwave Doppler radar sensor

BACKGROUND

Heart rate is one of the most crucial vital signs and can be measured remotely using microwave Doppler radar. As the distance between the body and the Doppler radar sensor increases, the output signal weakens, making it difficult to extract heartbeat waveforms. In this study, we propose a new template-matching method that addresses this issue by simulating Doppler radar signals. This method extracts the heartbeat waveform with higher accuracy while the participant is naturally sitting in a chair.

METHODS

An extended triangular wave model was created as a mathematical representation of cardiac physiology, taking into account heart movements. The Doppler radar output signal was then simulated based on this model to automatically obtain a template for one cycle. The validity of the proposed method was confirmed by calculating the PPIs using the template and comparing their accuracy to the R-R intervals (RRIs) of the electrocardiogram for five participants and by analyzing the signals of eight participants in their natural state using the mathematical model of heart movements. All measurements were conducted from a distance of 500 mm.

RESULTS

The correlation coefficients between the RRIs of the electrocardiogram and the PPIs using the proposed method were examined for five participants. The correlation coefficients were 0.93 without breathing and 0.70 with breathing. This demonstrates a higher correlation considering the long distance of 500 mm, and the fact that body movements were not specifically restricted, suggesting that the proposed method can successfully estimate RRI. The average correlation coefficients, calculated between the Doppler output signals and the templates for each of the eight participants, exceeded 0.95. Overall, the proposed method showed higher correlation coefficients than those reported in previous studies, indicating that our method performed well in extracting heartbeat waveforms.

CONCLUSIONS

Our results indicate that the proposed method of remote heart monitoring using microwave Doppler radar demonstrates higher accuracy in estimating the RRI of the electrocardiogram while at rest sitting in a chair, and the ability to extract the heartbeat waveforms from the measured Doppler output signal, eliminating the need to create templates in advance as required by conventional template matching methods. This approach offers more flexibility in the measurement environment than conventional methods.

Penetrating Barriers: Noncontact Measurement of Vital Bio Signs Using Radio Frequency Technology

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient's physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject's condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient's physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health.

Systematic Literature Review Regarding Heart Rate and Respiratory Rate Measurement by Means of Radar Technology

The use of radar technology for non-contact measurement of vital parameters is increasingly being examined in scientific studies. Based on a systematic literature search in the PubMed, German National Library, Austrian Library Network (Union Catalog), Swiss National Library and Common Library Network databases, the accuracy of heart rate and/or respiratory rate measurements by means of radar technology was analyzed. In 37% of the included studies on the measurement of the respiratory rate and in 48% of those on the measurement of the heart rate, the maximum deviation was 5%. For a tolerated deviation of 10%, the corresponding percentages were 85% and 87%, respectively. However, the quantitative comparability of the results available in the current literature is very limited due to a variety of variables. The elimination of the problem of confounding variables and the continuation of the tendency to focus on the algorithm applied will continue to constitute a central topic of radar-based vital parameter measurement. Promising fields of application of research can be found in particular in areas that require non-contact measurements. This includes infection events, emergency medicine, disaster situations and major catastrophic incidents.

An OpenCV-Based Approach for Automated Cardiac Rhythm Measurement in Zebrafish from Video Datasets

Cardiac arrhythmia has been defined as one of the abnormal heart rhythm symptoms, which is a common problem dealt with by cardiologists. Zebrafish were established as a powerful animal model with a transparent body that enables optical observation to analyze cardiac morphology and cardiac rhythm regularity. Currently, research has observed heart-related parameters in zebrafish, which used different approaches, such as starting from the use of fluorescent transgenic zebrafish, different software, and different observation methods. In this study, we developed an innovative approach by using the OpenCV library to measure zebrafish larvae heart rate and rhythm. The program is designed in Python, with the feature of multiprocessing for simultaneous region-of-interest (ROI) detection, covering both the atrium and ventricle regions in the video, and was designed to be simple and user-friendly, having utility even for users who are unfamiliar with Python. Results were validated with our previously published method using ImageJ, which observes pixel changes. In summary, the results showed good consistency in heart rate-related parameters. In addition, the established method in this study also can be widely applied to other invertebrates (like Daphnia) for cardiac rhythm measurement.

Portable Micro-Doppler Radar with Quadrature Radar Architecture for Non-Contact Human Breath Detection

Recently, rapid advances in radio detection and ranging (radar) technology applications have been implemented in various fields. In particular, micro-Doppler radar has been widely developed to perform certain tasks, such as detection of buried victims in natural disaster, drone system detection, and classification of humans and animals. Further, micro-Doppler radar can also be implemented in medical applications for remote monitoring and examination. This paper proposes a human respiration rate detection system using micro-Doppler radar with quadrature architecture in the industrial, scientific, and medical (ISM) frequency of 5.8 GHz. We use a mathematical model of human breathing to further explore any insights into signal processes in the radar. The experimental system is designed using the USRP B200 mini-module as the main component of the radar and the Vivaldi antennas working at 5.8 GHz. The radar system is integrated directly with the GNU Radio Companion software as the processing part. Using a frequency of 5.8 GHz and USRP output power of 0.33 mW, our proposed method was able to detect the respiration rate at a distance of 2 m or less with acceptable error. In addition, the radar system could differentiate different frequency rates for different targets, demonstrating that it is highly sensitive. We also emphasize that the designed radar system can be used as a portable device which offers flexibility to be used anytime and anywhere.

Motion-Tolerant Non-Contact Heart-Rate Measurements from Radar Sensor Fusion

Microwave radar technology is very attractive for ubiquitous short-range health monitoring due to its non-contact, see-through, privacy-preserving and safe features compared to the competing remote technologies such as optics. The possibility of radar-based approaches for breathing and cardiac sensing was demonstrated a few decades ago. However, investigation regarding the robustness of radar-based vital-sign monitoring (VSM) is not available in the current radar literature. In this paper, we aim to close this gap by presenting an extensive experimental study of vital-sign radar approach. We consider diversity in test subjects, fitness levels, poses/postures, and, more importantly, random body movement (RBM) in the study. We discuss some new insights that lead to robust radar heart-rate (HR) measurements. A novel active motion cancellation signal-processing technique is introduced, exploiting dual ultra-wideband (UWB) radar system for motion-tolerant HR measurements. Additionally, we propose a spectral pruning routine to enhance HR estimation performance. We validate the proposed method theoretically and experimentally. Totally, we record and analyze about 3500 seconds of radar measurements from multiple human subjects.

Evaluation of Optical and Radar Based Motion Capturing Technologies for Characterizing Hand Movement in Rheumatoid Arthritis-A Pilot Study

In light of the state-of-the-art treatment options for patients with rheumatoid arthritis (RA), a detailed and early quantification and detection of impaired hand function is desirable to allow personalized treatment regiments and amend currently used subjective patient reported outcome measures. This is the motivation to apply and adapt modern measurement technologies to quantify, assess and analyze human hand movement using a marker-based optoelectronic measurement system (OMS), which has been widely used to measure human motion. We complement these recordings with data from markerless (Doppler radar) sensors and data from both sensor technologies are integrated with clinical outcomes of hand function. The technologies are leveraged to identify hand movement characteristics in RA affected patients in comparison to healthy control subjects, while performing functional tests, such as the Moberg-Picking-Up Test. The results presented discuss the experimental framework and present the limiting factors imposed by the use of marker-based measurements on hand function. The comparison of simple finger motion data, collected by the OMS, to data recorded by a simple continuous wave radar suggests that radar is a promising option for the objective assessment of hand function. Overall, the broad scope of integrating two measurement technologies with traditional clinical tests shows promising potential for developing new pathways in understanding of the role of functional outcomes for the RA pathology.

Vital-Signs Detector Based on Frequency-Shift Keying Radar

A frequency-shift keying (FSK) radar in the 2.45-GHz band is proposed for highly accurate vital-signs detection. The measurement accuracy of the proposed detector for the heartbeat is increased by using the cross-correlation between the phase differences of signals at two frequencies used by the FSK radar, which alternately transmits and receives the signals with different frequencies. Two frequencies—2.45 and 2.5 GHz—are effectively discriminated by using the envelope detection with the frequency control signal of the signal generator in the output waveform of the FSK radar. The phase difference between transmitted and received signals at each frequency is determined after calibrating the I/Q imbalance and direct-current offset using a data-based imbalance compensation algorithm, the Gram–Schmidt procedure, and the Pratt method. The absolute-distance measurement results for a human being show that the vital signs obtained at each frequency using the proposed FSK radar have a cross-correlation. The heartbeat detection results for the proposed FSK radar at a distance of < 2.4 m indicate a reduction in the error rate and an increase in the signal-to-noise ratio compared with those obtained using a single operating frequency.

Radar-Based Non-Contact Continuous Identity Authentication

Non-contact vital signs monitoring using microwave Doppler radar has shown great promise in healthcare applications. Recently, this unobtrusive form of physiological sensing has also been gaining attention for its potential for continuous identity authentication, which can reduce the vulnerability of traditional one-pass validation authentication systems. Physiological Doppler radar is an attractive approach for continuous identity authentication as it requires neither contact nor line-of-sight and does not give rise to privacy concerns associated with video imaging. This paper presents a review of recent advances in radar-based identity authentication systems. It includes an evaluation of the applicability of different research efforts in authentication using respiratory patterns and heart-based dynamics. It also identifies aspects of future research required to address remaining challenges in applying unobtrusive respiration-based or heart-based identity authentication to practical systems. With the advancement of machine learning and artificial intelligence, radar-based continuous authentication can grow to serve a wide range of valuable functions in society.

Non-contact and real-time measurement of heart rate and heart rate variability using microwave reflectometry

In this paper, we present noncontact and noninvasive vital signal detection using a microwave reflectometer. Elimination of noise components due to random movement of human subjects has been the biggest issue for microwave measurement. Appropriate filtering, amplitude control of the reflectometer signal, and cross correlation among multiple reflectometers together with new algorithms have enabled motion artifact elimination, signal peak detection, and data processing for various parameters related to heart rate (HR) and heart rate variability (HRV). We focus here on the real time measurements of instantaneous HR and HRV for practical use. The evaluation by microwave reflectometry is completely noninvasive and feasible even through clothing, which is extremely effective for health maintenance in daily life as well as for preventing sudden death related to, for example, coronary heart disease and ventricular arrhythmia.

A Novel Signal Separation and De-Noising Technique for Doppler Radar Vital Signal Detection

Doppler radar for monitoring vital signals is an emerging tool, and how to remove the noise during the detection process and reconstruct the accurate respiration and heartbeat signals are hot issues in current research. In this paper, a novel radar vital signal separation and de-noising technique based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sample entropy (SampEn), and wavelet threshold is proposed. First, the noisy radar signal was decomposed into a series of intrinsic mode functions (IMFs) using ICEEMDAN. Then, each IMF was analyzed using SampEn to find out the first few IMFs containing noise, and these IMFs were de-noised using the wavelet threshold. Finally, in order to extract accurate vital signals, spectrum analysis and Kullback-Leible (KL) divergence calculations were performed on all IMFs, and appropriate IMFs were selected to reconstruct respiration and heartbeat signals. Moreover, as far as we know, there is almost no previous research on radar vital signal de-noising based on the proposed technique. The effectiveness of the algorithm was verified using simulated and measured experiments. The results show that the proposed algorithm could effectively reduce the noise and was superior to the existing de-noising technologies, which is beneficial for extracting more accurate vital signals.

Separation of Respiratory Signatures for Multiple Subjects Using Independent Component Analysis with the JADE Algorithm

Respiration monitoring using microwave Doppler radar has attracted significant interest over the last four decades due to its non-invasive and non-contact form of measurement. However, this technology is still not at the level of practical implementations in healthcare due to motion artifacts and interference from multiple subjects within the range of the Doppler radar sensor. Most reported results in literature focus only on single subject measurements because when multiple subjects are present there are interfering respiration signals which are difficult to separate as individual respiration signals. This paper investigates the feasibility of separating respiratory signatures from the multiple subjects. We employed a new approach using Independent Component Analysis (ICA) with the Joint Approximate Diagonalization of Eignematrices (JADE) algorithm to achieve this for closely spaced subjects, and the system is also capable of estimating Direction of Arrival (DOA) for well-spaced subjects. Experimental results demonstrated that the ICA-JADE method can separate respiratory signatures from two subjects one meter apart from each other at a distance from the radar of 2.89 meters. The separated respiratory pattern closely correlates with reference chest belt respiration patterns, and the mean square error is approximately 11.58%. Concisely, this paper clearly demonstrates that by integrating ICA with the JADE algorithm in a Doppler radar physiological monitoring system, multiple subjects can be monitored simultaneously.

Portable Microwave Radar Systems for Short-Range Localization and Life Tracking: A Review

Short-range localization and life tracking have been hot research topics in the fields of medical care, consumer electronics, driving assistance, and indoor robots/drones navigation. Among various sensors, microwave and mm-wave continuous-wave (CW) radar sensors are gaining more popularity in their intrinsic advantages such as simple architecture, easy system integration, high accuracy, relatively low cost, and penetration capability. This paper reviews the recent advances in CW radar systems for short-range localization and life tracking applications, including system improvement, signal processing, as well as the emerging applications integrated with machine learning.

Experimental Study of Wireless Monitoring of Human Respiratory Movements Using UWB Impulse Radar Systems

This paper analyzes and discusses the capability of human being detection using impulse ultra-wideband (UWB) radar with an improved detection algorithm. The multiple automatic gain control (AGC) technique is employed to enhance the amplitudes of human respiratory signals. Two filters with seven values averaged are used to further improve the signal-to-noise ratio (SNR) of the human respiratory signals. The maximum slope and standard deviation are used for analyzing the characteristics of the received pulses, which can provide two distance estimates for human being detection. Most importantly, based on the two distance estimates, we can accurately judge whether there are human beings in the detection environments or not. The data size can be reduced based on the defined interested region, which can improve the operation efficiency of the radar system for human being detection. The developed algorithm provides excellent performance regarding human being detection, which is validated through comparison with several well-known algorithms.

Robust real-time heart rate prediction for multiple subjects from facial video using compressive tracking and support vector machine

Remote monitoring of vital physiological signs allows for unobtrusive, nonrestrictive, and noncontact assessment of an individual's health. We demonstrate a simple but robust image photoplethysmography-based heart rate (HR) estimation method for multiple subjects. In contrast to previous studies, a self-learning procedure of tech was developed in our study. We improved compress tracking algorithm to track the regions of interest from video sequences and used support vector machine to filter out potentially false beats caused by variations in the reflected light from the face. The experiment results on 40 subjects show that the absolute value of mean error reduces from 3.6 to 1.3  beats/min . We further explore experiments for 10 subjects simultaneously, regardless of the videos at a resolution of 600 by 800, the HR is predicted real-time and the results reveal modest but significant effects on HR prediction.

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar.

Short-Range Noncontact Sensors for Healthcare and Other Emerging Applications: A Review

Short-range noncontact sensors are capable of remotely detecting the precise movements of the subjects or wirelessly estimating the distance from the sensor to the subject. They find wide applications in our day lives such as noncontact vital sign detection of heart beat and respiration, sleep monitoring, occupancy sensing, and gesture sensing. In recent years, short-range noncontact sensors are attracting more and more efforts from both academia and industry due to their vast applications. Compared to other radar architectures such as pulse radar and frequency-modulated continuous-wave (FMCW) radar, Doppler radar is gaining more popularity in terms of system integration and low-power operation. This paper reviews the recent technical advances in Doppler radars for healthcare applications, including system hardware improvement, digital signal processing, and chip integration. This paper also discusses the hybrid FMCW-interferometry radars and the emerging applications and the future trends.

Estimation of physiological sub-millimeter displacement with CW Doppler radar

Doppler radar physiological sensing has been studied for non-contact detection of vital signs including respiratory and heartbeat rates. This paper presents the first micrometer resolution Wi-Fi band Doppler radar for sub-millimeter physiological displacement measurement. A continuous-wave Doppler radar working at 2.4GHz is used for the measurement. It is intended for estimating small displacements on the body surface resulting from physiological activity. A mechanical mover was used as target, and programmed to conduct sinusoidal motions to simulate pulse motions. Measured displacements were compared with a reference system, which indicates a superior performance in accuracy for having absolute errors less than 10μm, and relative errors below 4%. It indicates the feasibility of highly accurate non-contact monitoring of physiological movements using Doppler radar.

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

Novel nonintrusive technologies for wrist pulse detection have been developed and proposed as systems for sleep monitoring using three types of radio frequency (RF) sensors. The three types of RF sensors for heart rate measurement on wrist are a flexible RF single resonator, array resonators, and an injection-locked PLL resonator sensor. To verify the performance of the new RF systems, we compared heart rates between presleep time and postsleep onset time. Heart rates of ten subjects were measured using the RF systems during sleep. All three RF devices detected heart rates at 0.2 to 1 mm distance from the skin of the wrist over clothes made of cotton fabric. The wrist pulse signals of a flexible RF single resonator were consistent with the signals obtained by a portable piezoelectric transducer as a reference. Then, we confirmed that the heart rate after sleep onset time significantly decreased compared to before sleep. In conclusion, the RF system can be utilized as a noncontact nonintrusive method for measuring heart rates during sleep.

A machine learning approach to improve contactless heart rate monitoring using a webcam

Unobtrusive, contactless recordings of physiological signals are very important for many health and human-computer interaction applications. Most current systems require sensors which intrusively touch the user's skin. Recent advances in contact-free physiological signals open the door to many new types of applications. This technology promises to measure heart rate (HR) and respiration using video only. The effectiveness of this technology, its limitations, and ways of overcoming them deserves particular attention. In this paper, we evaluate this technique for measuring HR in a controlled situation, in a naturalistic computer interaction session, and in an exercise situation. For comparison, HR was measured simultaneously using an electrocardiography device during all sessions. The results replicated the published results in controlled situations, but show that they cannot yet be considered as a valid measure of HR in naturalistic human-computer interaction. We propose a machine learning approach to improve the accuracy of HR detection in naturalistic measurements. The results demonstrate that the root mean squared error is reduced from 43.76 to 3.64 beats/min using the proposed method.

Assessment of human respiration patterns via noncontact sensing using Doppler multi-radar system

Human respiratory patterns at chest and abdomen are associated with both physical and emotional states. Accurate measurement of the respiratory patterns provides an approach to assess and analyze the physical and emotional states of the subject persons. Not many research efforts have been made to wirelessly assess different respiration patterns, largely due to the inaccuracy of the conventional continuous-wave radar sensor to track the original signal pattern of slow respiratory movements. This paper presents the accurate assessment of different respiratory patterns based on noncontact Doppler radar sensing. This paper evaluates the feasibility of accurately monitoring different human respiration patterns via noncontact radar sensing. A 2.4 GHz DC coupled multi-radar system was used for accurate measurement of the complete respiration patterns without any signal distortion. Experiments were carried out in the lab environment to measure the different respiration patterns when the subject person performed natural breathing, chest breathing and diaphragmatic breathing. The experimental results showed that accurate assessment of different respiration patterns is feasible using the proposed noncontact radar sensing technique.

Non-invasive UWB sensing of astronauts' breathing activity

The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed.

Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor

The designed sensor enables accurate reconstruction of chest-wall movement caused by cardiopulmonary activities, and the algorithm enables estimation of respiration, heartbeat rate, and some indicators of heart rate variability (HRV). In particular, quadrature receiver and arctangent demodulation with calibration are introduced for high linearity representation of chest displacement; 24-bit ADCs with oversampling are adopted for radar baseband acquisition to achieve a high signal resolution; continuous-wavelet filter and ensemble empirical mode decomposition (EEMD) based algorithm are applied for cardio/pulmonary signal recovery and separation so that accurate beat-to-beat interval can be acquired in time domain for HRV analysis. In addition, the wireless sensor is realized and integrated on a printed circuit board compactly. The developed sensor system is successfully tested on both simulated target and human subjects. In simulated target experiments, the baseband signal-to-noise ratio (SNR) is 73.27 dB, high enough for heartbeat detection. The demodulated signal has 0.35% mean squared error, indicating high demodulation linearity. In human subject experiments, the relative error of extracted beat-to-beat intervals ranges from 2.53% to 4.83% compared with electrocardiography (ECG) R-R peak intervals. The sensor provides an accurate analysis for heart rate with the accuracy of 100% for p = 2% and higher than 97% for p = 1%.

A Portable Infection Screening System Designed for Onboard Entry Screening Based on Multi-Parameter Vital Signs

After outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantines adopted fever-based screening to identify infected individuals using infrared thermography to control global pandemic. Unfortunately, the sensitivity of fever-based screening system did not exceed 70.4% at Narita International Airport. In order to achieve accurate onboard entry screening for highly contagious infectious diseases, the authors developed a portable system designed for onboard entry screening with linear discriminant analysis. Within several tens of seconds, the system automatically discriminates infected individuals from normal subjects using measured heart rate, respiratory rate, as well as facial surface temperature determined by thermography. The size of system is small enough to be placed on airplane tray tables. The authors tested on 68 subjects including 12 influenza patients to evaluate the system. The result showed sensitivity of 91.7% and specificity of 92.9%. The system seems to be promising for onboard infection screening to safeguard public health.

Parametric study of antennas for long range Doppler radar heart rate detection

This research presents results obtained from long range measurements of physiological motion pertaining to human cardiac and respiration activity. A pulse pressure sensor was used as reference to verify the results from radar signals. A motion detection and grading algorithm was used to detect the presence of heart rate. In addition to showing that human heart rate and respiration can be measured at distances of 21 and 69 meters respectively, the effect of antenna size, radiation pattern and gain on the range of the radar has also been studied.

Vital signs: asthma prevalence, disease characteristics, and self-management education: United States, 2001--2009

BACKGROUND

Most persons with asthma can be symptom-free if they receive appropriate medical care, use inhaled corticosteroids when prescribed, and modify their environment to reduce or eliminate exposure to allergens and irritants. This report reviews recent progress in managing asthma and reducing its prevalence in the United States.

METHODS

CDC analyzed asthma data from the 2001--2009 National Health Interview Survey concerning children and adults, and from the 2001, 2005, and 2009 state-based Behavioral Risk Factor Surveillance System concerning adults.

RESULTS

Among persons of all ages, the prevalence of asthma increased from 7.3% (20.3 million persons) in 2001 to 8.2% (24.6 million persons) in 2009, a 12.3% increase. Prevalence among children (persons aged <18 years) was 9.6%, and was highest among poor children (13.5%) and among non-Hispanic black children (17.0%). Prevalence among adults was 7.7%, and was greatest in women (9.7%) and in adults who were poor (10.6%). More uninsured persons with asthma than insured could not afford to buy prescription medications (40.3% versus 11.5%), and fewer uninsured persons reported seeing or talking with a primary-care physician (58.8% versus 85.6%) or specialist (19.5% versus 36.9%). Among persons with asthma, 34.2% reported being given a written asthma action plan, and 68.1% had been taught the appropriate response to symptoms of an asthma attack. Only about one third of children or adults were using long-term control medicine such as inhaled corticosteroids at the time of the survey. CONCLUSIONS AND COMMENT: Persons with asthma need to have access to health care and appropriate medications and use them. They also need to learn self-management skills and practice evidence-based interventions that reduce environmental risk factors.

Measurement of heart rate variability and stress evaluation by using microwave reflectometric vital signal sensing

In this paper, we present two robust signal processing techniques for stress evaluation using a microwave reflectometric cardiopulmonary sensing instrument. These techniques enable the heart rate variability (HRV) to be recovered from measurements of body-surface dynamic motion, which is subsequently used for the stress evaluation. Specifically, two novel elements are introduced: one is a reconfiguration of the HRV from the cross-correlation function between a measurement signal and a template signal which is constructed by averaging periodic component over a measurement time. The other is a reconstruction of the HRV from the time variation of the heartbeat frequency; this is evaluated by a repetition of the maximum entropy method. These two signal processing techniques accomplish the reconstruction of the HRV, though they are completely different algorithms. For validations of our model, an experimental setup is presented and several sets of experimental data are analyzed using the two proposed signal processing techniques, which are subsequently used for the stress evaluation. The results presented herein are consistent with electrocardiogram data.

A novel screening method for influenza patients using a newly developed non-contact screening system

OBJECTIVES

In places of mass gathering, rapid infection screening prior to definite diagnosis is vital during the epidemic season of a novel influenza. In order to assess the possibility of clinical application of a newly developed non-contact infection screening system, we conducted screening for influenza patients.

MATERIALS AND METHODS

The system is operated by a screening program via a linear discriminant analysis using non-contact derived variables, i.e., palmar pulse derived from a laser Doppler blood-flow meter, respiration rate determined by a 10-GHz microwave radar, and average facial temperature measured by thermography. The system was tested on 57 seasonal influenza (2008-2009) patients (35.7 degrees C < or = body temperature < or = 38.3 degrees C, 19-40 years) and 35 normal control subjects (35.5 degrees C < or = body temperature < or = 36.9 degrees C, 21-35 years) at the Japan Self-defense Forces Central Hospital.

RESULTS

A significant linear discriminant function (p < 0.001) was determined to distinguish the influenza group from the control group (Mahalanobis D-square = 6.5, classification error rate > 10%). The system had a positive predictive value (PPV) of 93%, which is higher than the PPV value (PPV < or = 65.4%) reported in the recent summary of studies using only thermography performed mainly in hospitals.

CONCLUSIONS

The proposed system appears promising for application in accurate screening for influenza patients at places of mass gathering.

Performance assessment techniques for Doppler radar physiological sensors

This paper presents a technique for assessing the performance of continuous wave Doppler radar systems for physiological sensing. The technique includes an artificial target for testing physiological sensing radar systems with motion analogous to human heart movement and software algorithms leveraging the capabilities of this target to simply test radar system performance. The mechanical target provides simple to complex patterns of motion that are stable and repeatable. Details of radar system performance can be assessed and the effects of configuration changes that might not appear with a human target can be observed when using this mechanical target.

Development of a non-contact screening system for rapid medical inspection at a quarantine depot using a laser Doppler blood-flow meter, microwave radar and infrared thermography

In order to conduct fast screening of passengers with infections such as severe acute respiratory syndrome (SARS) or pandemic influenza at a quarantine depot, we developed a non-contact screening system with a self-produced program to conduct a human screening within five seconds, via a linear discriminant function from non-contact derived variables, i.e. palmer pulse derived from a laser Doppler blood-flow meter, respiration rate determined by a 10-GHz microwave radar, and facial temperature measured by a thermography. The system evaluation was conducted on seven healthy male subjects (23+1 years). In order to achieve a pseudo-infection condition, the subjects maintained an ergo-meter exercise load (100 W, 10 minutes). Before (normal condition) and after (pseudo-infection condition) exercise, a significant linear discriminant function (p50.001) was determined to distinguish the pseudo-infection condition from the normal condition (Mahalanobis D-square 1/4 20.3, classification error rate55%). The proposed system appears promising for future application in fast screening of infection at a quarantine depot.

Development of a noncontact and long-term respiration monitoring system using microwave radar for hibernating black bear

The aim of this study is to develop a prototype system for noncontact, noninvasive and unconstrained vital sign monitoring using microwave radar and to use the system to measure the respiratory rate of a Japanese black bear (Ursus thibetanus japonicus) during hibernation for ensuring the bear's safety. Ueno Zoological Gardens in Tokyo planned to help the Japanese black bear (female, approximately 2 years of age) going into hibernation. The prototype system has a microwave Doppler radar antenna (10-GHz frequency, approximately 7 mW output power) for measuring motion of the body surface caused by respiratory activity without making contact with the body. Monitoring using this system was conducted from December 2006 to April 2007. As a result, from December 18, 2006, to March 17, 2007, similar behaviors reported by earlier studies were observed, such as sleeping with curled up posture and not eating, urinating or defecating. During this hibernation period and also around the time of hibernation, the prototype system continuously measured cyclic oscillations. The presence of cyclic vibrations at 8-sec intervals (about 7 bpm) was confirmed by the system before she entered hibernation on December 3, 2006. The respiratory rate gradually decreased, and during the hibernation period the respiratory rate was extremely low at approximately 2 bpm with almost no change. The results show that motion on the body surface caused by respiratory activity can be measured without touching the animal's body. Thus, the microwave radar employed here can be utilized as an aid in observing vital signs of animals.

A remote compact sensor for the real-time monitoring of human heartbeat and respiration rate

A remote compact sensor system for the detection of human vital signs (heartbeat and respiration rate) is presented. The frequency band of 24 GHz is employed for remote sensing. For the compact size, the developed sensor uses a circularly polarized electromagnetic wave with a single antenna. The sensor system is composed of radio-frequency circuits, a signal conditioning block, a data-acquisition unit, and a signal-processing part. The peak detection of the power spectral density with a tracking algorithm is utilized for the real-time detection of human vital signs. The measurement result is compared with the commercial fingertip sensor. The comparison result shows excellent agreement.

Noninvasive biosignal detection radar system using circular polarization

This paper proposes an integrated hypersensitive Doppler radar system through a circular polarization characteristic. Through the idea of a reverse sense of rotation when the reflecting surface is perfectly conducting, it is shown that the detecting property of the system can be effectively improved by using antennas that have a reverse polarization. This bistatic radar system can be used in noninvasively sensing biosignals such as respiration and heart rates with the periodic movement of skin and muscle near the heart. The operating frequency of the system is in the X-band and the radar size is 95 x50 x13 mm(3).

Study of the ballistocardiogram signal in life detection system based on radar

In this article, our study of non-contact method via radar for monitoring the heart and respiratory rates of human subject is reported. The system is constructed which synchronously detects the electrocardiogram signals by the electrocardiograph and the ballistocardiogram signals by the non-contact life parameter detecting technology. Also, the detected signals are analyzed respectively in the time and frequency domain. The results show that the cycle of the ballistocardiogram is obvious in time domain and that the rhythm of the two kinds of signals keeps consistent. And their characteristic points in frequency domain are also the same. The clinical medicine usefulness of ballistocardiogram detected by the non-contact technology is approved and the credible evidence for the succeeding signal analysis and the clinical application is provided. Furthermore, the characters of the heartbeat signal detected by our system and the reasons for that are also discussed in detail in our paper.

Non-contact respiratory monitoring system using a ceiling-attached microwave antenna

Using a microwave antenna attached to the room ceiling, we conducted non-contact monitoring of respiratory chest wall motions of subjects in bed and covered by a soft comfortable bedding, to measure the vital signs of patients under nursing care in a welfare institution. Long-term vital sign monitoring using electrodes places a heavy burden on monitored individuals. Our non-contact respiratory monitoring system comprises a 1,215 MHz-microwave radar (LDR-1), antenna box attached to the ceiling, and personal computer with analyzing software. The system was tested on eight healthy volunteers (mean age, 25 years; range, 21-44 years) and eight elderly volunteers with some disorders (mean age, 69 years; range, 66-75 years). Respiratory rates of subjects measured using this system correlated with rates measured using respiration sensors (r=0.97, P<0.001 for healthy volunteers, r=0.98, P<0.0001 for elderly volunteers). The system could monitor subtle changes in respiratory rate, and monitoring respiratory rate increases caused by disorders such as pneumonia will be possible.

A novel apparatus for non-contact measurement of heart rate variability: a system to prevent secondary exposure of medical personnel to toxic materials under biochemical hazard conditions, in monitoring sepsis or in predicting multiple organ dysfunction syndrome

BACKGROUND

The impaired balance of the low-frequency/high-frequency ratio obtained from spectral components of RR intervals can be a diagnostic test for sepsis. In addition, it is known that a reduction of heart rate variability (HRV) is useful in identifying septic patients at risk of the development of multiple organ dysfunction syndrome (MODS). We have reported a non-contact method using a microwave radar to monitor the heart and respiratory rates of a healthy person placed inside an isolator or of experimental animals exposed to toxic materials.

APPARATUS DESIGN AND TESTING

With the purpose of preventing secondary exposure of medical personnel to toxic materials under biochemical hazard conditions, we designed a novel apparatus for non-contact measurement of HRV using a 1215 MHz microwave radar, a high-pass filter, and a personal computer. The microwave radar monitors only the small reflected waves from the subject's chest wall, which are modulated by the cardiac and respiratory motion. The high-pass filter enhances the cardiac signal and attenuates the respiratory signal. In a human trial, RR intervals derived from the non-contact apparatus significantly correlated with those derived from ECG (r=0.98, P<0.0001). The non-contact apparatus showed a similar power spectrum of RR intervals to that of ECG.

CONCLUSIONS

Our non-contact HRV measurement apparatus appears promising for future pre-hospital monitoring of septic patients or for predicting MODS patients, inside isolators or in the field for mass casualties under biochemical hazard circumstances.

Non-contact determination of vital sign alterations in hypovolaemic states induced by massive haemorrhage: an experimental attempt to monitor the condition of injured persons behind barriers or under disaster rubble

To assess a non-contact method to determine the physical alteration of human subjects confined behind a barrier or under disaster rubble, an experimental, non-contact monitoring system was tested on rabbits in a hypovolaemic state. New Zealand male rabbits behind a barrier were subjected to hypovolaemic shock induced by the withdrawal of arterial blood (2ml per 100g body weight). The hypovolaemic state was determined by linear discriminant analysis using non-contact-derived variables: heart rate X1 and respiratory rate X2. Sixteen rabbits were equally divided between the hypovolaemic and control groups. To obtain the heart and respiratory rates simultaneously, the fast Fourier transform (FFT) was performed on the 1215MHz microwave radar analogue output. The linear discriminant function calculated by non-contact-derived variables was negative in the eight hypovolaemic rabbits and positive in the eight controls, so that the linear discriminant function could distinguish the hypovolaemic group from the control group. The Mahalanobis D-square (an index for classification accuracy) was 5908; the classification error rate corresponding to this value was small and negligible. The hypovolaemic rabbits developed metabolic acidosis (HCO3- 18.6+/-11.1 mmol l(-1) and pH 7.15+/-0.18 in arterial blood). The systolic blood pressure of the hypovolaemic group and the control was 56+/-4 and 83+/-6 mmHg, respectively (p < 0.01). The proposed method appears promising for applications to monitor the condition of human subjects behind barriers or under disaster rubble.

A Novel Method to Prevent Secondary Exposure of Medical and Rescue Personnel to Toxic Materials Under Biochemical Hazard Conditions Using Microwave Radar and Infrared Thermography

In order to prevent secondary exposure of medical personnel to toxic materials under biochemical hazard conditions, we performed a noncontact determination of exposure to toxic conditions via 1215-MHz microwave radar and thermography. A toxic condition was induced by intravenous administration of lipopolysaccharide (LPS) in rabbits. The exposure to LPS was determined by linear discriminant analysis using non-contact derived variables.

Microwave life-detection systems for searching human subjects under earthquake rubble or behind barrier

A new sensitive microwave life-detection system which can be used to locate human subjects buried under earthquake rubble or hidden behind various barriers has been constructed. This system operating at 1150 MHz or 450 MHz can detect the breathing and heartbeat signals of human subjects through an earthquake rubble or a construction barrier of about 10-ft thickness. The basic physical principle for the operation of a microwave life-detection system is rather simple. When a microwave beam of appropriate frequency (L or S band) is aimed at a pile of earthquake rubble covering a human subject or illuminated through a barrier obstructing a human subject, the microwave beam can penetrate the rubble or the barrier to reach the human subject. When the human subject is illuminated by a microwave beam, the reflected wave from the human subject will be modulated by the subject's body movements, which include the breathing and the heartbeat. If the clutter consisting of the reflected wave from stationary background can be completely eliminated and the reflected wave from the human subject's body is properly modulated, the breathing and heartbeat signals of the subject can be extracted. Thus, a human subject buried under earthquake rubble or hidden behind barriers can be located. This system has been tested extensively in a simulated earthquake rubble in the laboratory and also in a field test using realistic earthquake rubble conducted by a Federal Emergency Management Agency (FEMA) Task Force.

Microwave sensing of physiological movement and volume change: a review

The ability non-invasively to detect and monitor the movement of tissues and organs from outside the body provides many worthwhile areas of potential biomedical applications. Several non-invasive microwave techniques for contact and remote sensing of circulatory and respiratory movements and volume changes have been developed. In general, these systems consist of a microwave generator, a sampling device, a transmitting-receiving antenna, a set of signal-conditioning and processing devices, and a display unit. They operate at continuous-wave frequencies between 1 and 35 GHz and make use of amplitude and phase information derived from the received signal. The average power density of energy radiated by present systems ranges from approximately 0.001-1.0 mW/cm2. These systems are capable of registering instantaneous changes in fluid volume, pressure pulse, heart rate, and respiration rate in contact with body surface or at distances greater than 30 m, or behind thick layers of non-conductive walls.