Microwave Doppler Radar for Heartbeat Detection Vs Electrocardiogram

International audienceThis paper presents a contact-less system to detect the heartbeat activity from a distance of one meter. The proposed system is based on using a vector network analyzer. Measurements are performed at 16 GHz for different power levels between 0 and -25 dBm. Results for two S-parameters are obtained and compared to an ECG simultaneous signal in terms of heartbeat rate and heart rate variability

A long-range and long-life telemetry data-acquisition system for heart rate and multiple body temperatures from free-ranging animals

The system includes an implantable transmitter, external receiver-retransmitter collar, and a microprocessor-controlled demodulator. The size of the implant is suitable for animals with body weights of a few kilograms or more; further size reduction of the implant is possible. The ECG is sensed by electrodes designed for internal telemetry and to reduce movement artifacts. The R-wave characteristics are then specifically selected to trigger a short radio frequency pulse. Temperatures are sensed at desired locations by thermistors and then, based on a heartbeat counter, transmitted intermittently via pulse interval modulation. This modulation scheme includes first and last calibration intervals for a reference by ratios with the temperature intervals to achieve good accuracy even over long periods. Pulse duration and pulse sequencing are used to discriminate between heart rate and temperature pulses as well as RF interference

Position-Free Vital Sign Monitoring: Measurements and Processing

As traditional electrodes are perturbing for patients in critical cases such as for burn victims or newborn infants, and even to detect life sign under rubble, a contactless monitoring system for the life signs is a necessity. The aim of this chapter is to present a complete process used in detecting cardiopulmonary activities. This includes a microwave Doppler radar system that detects the body wall motion and signal processing techniques in order to extract the heartbeat rate. Measurements are performed at different positions simultaneously with a PC-based electrocardiogram (ECG). For a distance of 1 m between the subject and the antennas, measurements are performed for breathing subject at four positions: front, back, left, and right. Discrete wavelet transform is used to extract the heartbeat signal from the cardiopulmonary signal. The proposed system and signal processing techniques show high accuracy in detecting the cardiopulmonary signals and extracting the heartbeat rate

Doppler Radar for Heartbeat Rate and Heart Rate Variability Extraction

4 pagesInternational audienceThis paper presents a Doppler radar system used to detect the heartbeat signal from a d√istance of one meter. The proposed system is based on using a vector network analyzer and two antennas. Measurements are performed at 16 GHz for different power levels between 0 and -25 dBm. Both heartbeat rate and heart rate variability are extracted and compared to a simultaneous ECG signal

Intracranial Heart Rate Detection Using UWB Radar

Microwave imaging is a promising technique for noninvasive imaging of brain activity. A multistatic array of body coupled antennas and single chip pulsed ultra-wideband radars should be capable of detecting local changes in cerebral blood volume, a known indicator for neural activity. As an initial verification that small changes in the cerebrovascular system can indeed be measured inside the skull, we recorded the heart rate intracranially using a single radar module and two body coupled antennas. The obtained heart rate was found to correspond to ECG measurements. To confirm that the measured signal was indeed from within the skull, we performed simulations to predict the time-of-flight of radar pulses passing through different anatomical structures of the head. Simulated time-of-flight through the brain corresponded to the measured delay of heart rate modulation in the radar signal. The detection of intracranial heart rate using microwave techniques has not previously been reported, and serves as a first proof that functional neuroimaging using radar could lie within reach

Non Contact Heart Monitoring

Electrocardiograms are one of the most widely used methods for evaluating the structure-function relationships of the heart in health and disease. This book is the first of two volumes which reviews recent advancements in electrocardiography. This volume lays the groundwork for understanding the technical aspects of these advancements. The five sections of this volume, Cardiac Anatomy, ECG Technique, ECG Features, Heart Rate Variability and ECG Data Management, provide comprehensive reviews of advancements in the technical and analytical methods for interpreting and evaluating electrocardiograms. This volume is complemented with anatomical diagrams, electrocardiogram recordings, flow diagrams and algorithms which demonstrate the most modern principles of electrocardiography. The chapters which form this volume describe how the technical impediments inherent to instrument-patient interfacing, recording and interpreting variations in electrocardiogram time intervals and morphologies, as well as electrocardiogram data sharing have been effectively overcome. The advent of novel detection, filtering and testing devices are described. Foremost, among these devices are innovative algorithms for automating the evaluation of electrocardiograms. Permanenet links: Full chapter: http://www.intechopen.com/articles/show/title/non-contact-heart-monitoring Book: http://www.intechopen.com/books/show/title/advances-in-electrocardiograms-methods-and-analysi

Bio-Radar Applications for Remote Vital Signs Monitoring

Nowadays, most vital signs monitoring techniques used in a medical context and/or daily life routines require direct contact with skin, which can become uncomfortable or even impractical to be used regularly. Radar technology has been appointed as one of the most promising contactless tools to overcome these hurdles. However, there is a lack of studies that cover a comprehensive assessment of this technology when applied in real-world environments. This dissertation aims to study radar technology for remote vital signs monitoring, more specifically, in respiratory and heartbeat sensing. Two off-the-shelf radars, based on impulse radio ultra-wideband and frequency modu lated continuous wave technology, were customized to be used in a small proof of concept experiment with 10 healthy participants. Each subject was monitored with both radars at three different distances for two distinct conditions: breathing and voluntary apnea. Signals processing algorithms were developed to detect and estimate respiratory and heartbeat parameters, assessed using qualitative and quantitative methods. Concerning respiration, a minimum error of 1.6% was found when radar respiratory peaks signals were directly compared with their reference, whereas a minimum mean absolute error of 0.3 RPM was obtained for the respiration rate. Concerning heartbeats, their expression in radar signals was not as clear as the respiration ones, however a minimum mean absolute error of 1.8 BPM for heartbeat was achieved after applying a novel selective algorithm developed to validate if heart rate value was estimated with reliability. The results proved the potential for radars to be used in respiratory and heartbeat contactless sensing, showing that the employed methods can be already used in some mo tionless situations. Notwithstanding, further work is required to improve the developed algorithms in order to obtain more robust and accurate systems.Atualmente, a maioria das técnicas usadas para a monitorização de sinais vitais em contexto médicos e/ou diário requer contacto direto com a pele, o que poderá tornar-se incómodo ou até mesmo inviável em certas situações. A tecnologia radar tem vindo a ser apontada como uma das mais promissoras ferramentas para medição de sinais vitais à distância e sem contacto. Todavia, são necessários mais estudos que permitam avaliar esta tecnologia quando aplicada a situações mais reais. Esta dissertação tem como objetivo o estudo da tecnologia radar aplicada no contexto de medição remota de sinais vitais, mais concretamente, na medição de atividade respiratória e cardíaca. Dois aparelhos radar, baseados em tecnologia banda ultra larga por rádio de impulso e em tecnologia de onda continua modulada por frequência, foram configurados e usados numa prova de conceito com 10 participantes. Cada sujeito foi monitorizado com cada um dos radar em duas situações distintas: respirando e em apneia voluntária. Algorit mos de processamento de sinal foram desenvolvidos para detetar e estimar parâmetros respiratórios e cardíacos, avaliados através de métodos qualitativos e quantitativos. Em relação à respiração, o menor erro obtido foi de 1,6% quando os sinais de radar respiratórios foram comparados diretamente com os sinais de referência, enquanto que, um erro médio absoluto mínimo de 0,3 RPM foi obtido para a estimação da frequência respiratória via radar. A expressão cardíaca nos sinais radar não se revelou tão evidente como a respiratória, no entanto, um erro médio absoluto mínimo de 1,8 BPM foi obtido para a estimação da frequência cardíaca após a aplicação de um novo algoritmo seletivo, desenvolvido para validar a confiança dos valores obtidos. Os resultados obtidos provaram o potencial do uso de radares na medição de atividade respiratória e cardíaca sem contacto, sendo esta tecnologia viável de ser implementada em situações onde não existe muito movimento. Não obstante, os algoritmos desenvolvidos devem ser aperfeiçoados no futuro de forma a obter sistemas mais robustos e precisos

Remote Human Vital Sign Monitoring Using Multiple-Input Multiple-Output Radar at Millimeter-Wave Frequencies

Non-contact respiration rate (RR) and heart rate (HR) monitoring using millimeter-wave (mmWave) radars has gained lots of attention for medical, civilian, and military applications. These mmWave radars are small, light, and portable which can be deployed to various places. To increase the accuracy of RR and HR detection, distributed multi-input multi-output (MIMO) radar can be used to acquire non-redundant information of vital sign signals from different perspectives because each MIMO channel has different fields of view with respect to the subject under test (SUT). This dissertation investigates the use of a Frequency Modulated Continuous Wave (FMCW) radar operating at 77-81 GHz for this application. Vital sign signal is first reconstructed with Arctangent Demodulation (AD) method using phase change’s information collected by the radar due to chest wall displacement from respiration and heartbeat activities. Since the heartbeat signals can be corrupted and concealed by the third/fourth harmonics of the respiratory signals as well as random body motion (RBM) from the SUT, we have developed an automatic Heartbeat Template (HBT) extraction method based on Constellation Diagrams of the received signals. The extraction method will automatically spot and extract signals’ portions that carry good amount of heartbeat signals which are not corrupted by the RBM. The extracted HBT is then used as an adapted wavelet for Continuous Wavelet Transform (CWT) to reduce interferences from respiratory harmonics and RBM, as well as magnify the heartbeat signals. As the nature of RBM is unpredictable, the extracted HBT may not completely cancel the interferences from RBM. Therefore, to provide better HR detection’s accuracy, we have also developed a spectral-based HR selection method to gather frequency spectra of heartbeat signals from different MIMO channels. Based on this gathered spectral information, we can determine an accurate HR even if the heartbeat signals are significantly concealed by the RBM. To further improve the detection’s accuracy of RR and HR, two deep learning (DL) frameworks are also investigated. First, a Convolutional Neural Network (CNN) has been proposed to optimally select clean MIMO channels and eliminate MIMO channels with low SNR of heartbeat signals. After that, a Multi-layer Perceptron (MLP) neural network (NN) is utilized to reconstruct the heartbeat signals that will be used to assess and select the final HR with high confidence

Matrix pencil method for vital sign detection from signals acquired by microwave sensors

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

Novel Methods for Weak Physiological Parameters Monitoring.

M.S. Thesis. University of Hawaiʻi at Mānoa 2017