Noncontact Seismocardiogram Signal Detection Using Microwave Doppler Radar

The objective of the research is to achieve non-contact detection of seismocardiogram (SCG), a representation of mechanical heart motion, using microwave Doppler radar system. The increase in demand for health monitoring requires robust, reliable, and accurate remote detection of cardiac signals. Due to its ability to penetrate non-metal obstacles, microwave Doppler radar is promising to provide a non-contact and unobtrusive measurement. In this dissertation, both the hardware system and the signal processing approaches are developed for providing an accurate and reliable measurement of cardiac signals using the microwave Doppler radar. First, a noise suppression scheme and a clutter removal strategy are investigated to improve the performance of a microwave Doppler radar system. Then, an investigation is conducted to demonstrate the effectiveness of using a radar signal to represent SCG, and a standalone method is developed to extract the SCG features from the radar signal without using a contact electrocardiogram (ECG) signal that the conventional methods rely on. With the development of the hardware system and signal processing approaches, the complete non-contact measurement and analysis of cardiac signals can be achieved.Ph.D

Signal Processing Contributions to Contactless Monitoring of Vital Signs Using Radars

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living organism, and their assessment is the critical first step for any clinical evaluation. Monitoring vital sign information provides valuable insight into the patient's condition, including how they are responding to medical treatment and, more importantly, whether the patient is deteriorating. However, conventional contact-based devices are inappropriate for long-term continuous monitoring. Besides mobility restrictions and stress, they can cause discomfort, and epidermal damage, and even lead to pressure necrosis. On the other hand, the contactless monitoring of vital signs using radar devices has several advantages. Radar signals can penetrate through different materials and are not affected by skin pigmentation or external light conditions. Additionally, these devices preserve privacy, can be low-cost, and transmit no more power than a mobile phone. Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios. The challenge stems from the fact that when we breathe, or when the heart beats, the tiny induced motion of the chest wall surface can be smaller than one millimeter. This means that the vital sign information can be easily lost in the background noise, or even masked by additional body movements from the monitored subject. This thesis aims to propose innovative signal processing solutions to enable the contactless monitoring of vital signs in practical scenarios. Its main contributions are threefold: a new algorithm for recovering the chest wall movements from radar signals; a novel random body movement and interference mitigation technique; and a simple, yet robust and accurate, adaptive estimation framework. These contributions were tested under different operational conditions and scenarios, spanning ideal simulation settings, real data collected while imitating common working conditions in an office environment, and a complete validation with premature babies in a critical care environment. The proposed algorithms were able to precisely recover the chest wall motion, effectively reducing the interfering effects of random body movements, and allowing clear identification of different breathing patterns. This capability is the first step toward frequency estimation and early non-invasive diagnosis of cardiorespiratory problems. In addition, most of the time, the adaptive estimation framework provided breathing and heart rate estimates within the predefined error intervals, being capable of tracking the reference values in different scenarios. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a complete contactless solution for vital signs monitoring

Analysis of sandstone pore space fluid saturation and mineralogy variation via application of monostatic K-band frequency modulated continuous wave radar

In this paper we present the preliminary findings from a world first investigation into monostatic frequency modulated continuous wave (FMCW) radar analysis of porous sandstones and their fluid content. FMCW results, within 24 to 25.5 GHz, provide insights into the rock/pore system as well as into mineral and liquid distributions, both crucial for quantitative representation of the fluid-rock system for subsequent assessment of the sandstones. Sandstone samples, here characterised using known techniques of energy dispersive x-ray analysis, gaseous secondary electron and backscattered electron imaging are: Darney, Lazonby Locharbriggs and Red St. Bees sandstones, with FMCW results indicating that, in the K-Band, calculated values for relative permittivity, utilising free-space radiation reflection data, give results that are consistent with the known rock elemental constituents, where each sandstone has different distributions of the dominant quartz and subsidiary other minerals and of grain size and shape distributions. The experimental results support the sensitivity of this sensing modality to variances in rock properties in typical sandstones with complex relative permittivity, ε_r^*, values for unsaturated sandstones ranging from 5.76 to 6.76 and from 12.96 to 48.3 for partially saturated sandstones, with the highest values indicating high permittivity mineral inclusion and/or grain angularity

Bio-Radar: sistema de aquisição de sinais vitais sem contacto

The Bio-Radar system is capable to measure vital signs accurately, namely the respiratory and cardiac signal, using electromagnetic waves. In this way, it is possible to monitor subjects remotely and comfortably for long periods of time. This system is based on the micro-Doppler effect, which relates the received signal phase variation with the distance change between the subject chest-wall and the radar antennas, which occurs due to the cardiopulmonary function. Considering the variety of applications where this system can be used, it is required to evaluate its performance when applied to real context scenarios and thus demonstrate the advantages that bioradar systems can bring to the general population. In this work, a bio-radar prototype was developed in order to verify the viability to be integrated in specific applications, using robust and low profile solutions that equally guarantee the general system performance while addressing the market needs. Considering these two perspectives to be improved, different level solutions were developed. On the hardware side, textile antennas were developed to be embedded in a car seat upholstery, thus reaching a low profile solution and easy to include in the industrialization process. Real context scenarios imply long-term monitoring periods, where involuntary body motion can occur producing high amplitude signals that overshadow the vital signs. Non-controlled monitoring environments might also produce time varying parasitic reflections that have a direct impact in the signal. Additionally, the subject's physical stature and posture during the monitoring period can have a different impact in the signals quality. Therefore, signal processing algorithms were developed to be robust to low quality signals and non-static scenarios. On the other hand, the bio-radar potential can also be maximized if the acquired signals are used pertinently to help identify the subject's psychophysiological state enabling one to act accordingly. The random body motion until now has been seen as a noisy source, however it can also provide useful information regarding subject's state. In this sense, the acquired vital signs as well as other body motions were used in machine learning algorithms with the goal to identify the subject's emotions and thus verify if the remotely acquired vital signs can also provide useful information.O sistema Bio-Radar permite medir sinais vitais com precisão, nomeadamente o sinal respiratório e cardíaco, utilizando ondas eletromagnéticas para esse fim. Desta forma, é possível monitorizar sujeitos de forma remota e confortável durante longos períodos de tempo. Este sistema é baseado no efeito de micro-Doppler, que relaciona a variação de fase do sinal recebido com a alteração da distância entre as antenas do radar e a caixa torácica do sujeito, que ocorre durante a função cardiopulmonar. Considerando a variedade de aplicações onde este sistema pode ser utilizado, é necessário avaliar o seu desempenho quando aplicado em contextos reais e assim demonstrar as vantagens que os sistemas bio-radar podem trazer à população geral. Neste trabalho, foi desenvolvido um protótipo do bio radar com o objetivo de verificar a viabilidade de integrar estes sistemas em aplicações específicas, utilizando soluções robustas e discretas que garantam igualmente o seu bom desempenho, indo simultaneamente de encontro às necessidades do mercado. Considerando estas duas perspetivas em que o sistema pode ser melhorado, foram desenvolvidas soluções de diferentes níveis. Do ponto de vista de hardware, foram desenvolvidas antenas têxteis para serem integradas no estofo de um banco automóvel, alcançando uma solução discreta e fácil de incluir num processo de industrialização. Contextos reais de aplicação implicam períodos de monitorização longos, onde podem ocorrer movimentos corporais involuntários que produzem sinais de elevada amplitude que se sobrepõem aos sinais vitais. Ambientes de monitorização não controlados podem produzir reflexões parasitas variantes no tempo que têm impacto direto no sinal. Adicionalmente, a estrutura física do sujeito e a sua postura durante o período de monitorização podem ter impactos diferentes na qualidade dos sinais. Desta forma, foram desenvolvidos algoritmos de processamento de sinal robustos a sinais de baixa qualidade e a cenários não estáticos. Por outro lado, o potencial do bio radar pode também ser maximizado se os sinais adquiridos forem pertinentemente utilizados de forma a ajudar a identificar o estado psicofisiológico do sujeito, permitindo mais tarde agir em conformidade. O movimento corporal aleatório que foi até agora visto como uma fonte de ruído, pode no entanto também fornecer informação útil sobre o estado do sujeito. Neste sentido, os sinais vitais e outros movimentos corporais adquiridos foram utilizados em algoritmos de aprendizagem automática com o objetivo de identificar as emoções do sujeito e assim verificar que sinais vitais adquiridos remotamente podem também conter informação útil.Programa Doutoral em Engenharia Eletrotécnic

Generic Radar Processing Methods for Monitoring Tasks on Bridge Infrastructure

Kritische Verkehrsinfrastrukturen, wie z. B. Brücken, können nur dann sicher betrieben werden, wenn ihr Zustand regelmäßig bewertet wird. Neben visuellen Inspektionen umfasst die Bewertung auch Messungen des Brückenverhaltens auf statische oder dynamische Lasten. Diese Messungen werden in der Regel mit einer Vielzahl von Sensoren durchgeführt, die direkt an der Brücke befestigt sind. Zunehmend werden jedoch auch Fernerkundungssensoren eingesetzt, wie z.B. das bodenbasierte interferometrische Radar (engl.: ground-based interferometric radar - GBR). GBR können aus der Ferne Verschiebungen mit einer Genauigkeit im Submillimeterbereich messen, indem sie eine elektromagnetische Welle aussenden, die von Strukturen an der Unterseite der Brücke reflektiert wird. Im Vergleich zu direkt befestigten Sensoren wird die Installationszeit verkürzt und der normale Betrieb der Brücke wird nicht beeinträchtigt. Vergleichbare Messunsicherheiten lassen sich jedoch nur erreichen, wenn bei der Prozessierung der Messungen bestimmte Herausforderungen berücksichtigt werden. Dabei geht es vor allem um die Entfernung externer Einflüsse wie Störungen des Signals oder Veränderungen atmosphärischer Parameter. Die Messungen werden außerdem durch statischen Clutter und Projektionsfehler beeinflusst, die zu systematischen Abweichungen führen. Statischer Clutter wird mit einer angepassten Kreisschätzung bestimmt, während Projektionsfehler durch die Verwendung mehrerer Sensoren zur Schätzung separater Verschiebungskomponenten vermindert werden. Mit diesen zusätzlichen Prozessierungsschritten erreicht GBR eine ähnliche Unsicherheit wie andere Fernerkundungssensoren, was durch Vergleiche mit Referenzsensoren validiert wird. Verbleibende Unterschiede zu diesen Referenzsensoren lassen sich durch Unsicherheiten bei der Schätzung von Clutter und durch die begrenzte Auflösung einzelner Reflexionen erklären. Die resultierenden Verschiebungsmessungen werden dann zur Schätzung schadensempfindlicher Merkmale wie Eigenfrequenzen und Eigenformen verwendet. Eigenfrequenzen werden bestimmt, indem ein Modell einer gedämpften Sinuskurve für die Schwingung nach einer Fahrzeugüberfahrt geschätzt wird. Mit diesem Ansatz wird jede Fahrzeugüberfahrt separat analysiert, was eine Unterscheidung zwischen verschiedenen Fahrzeugmassen ermöglicht. Außerdem erlaubt die große Anzahl von Frequenzschätzungen eine zuverlässigere Bestimmung des Temperatureinflusses auf die Eigenfrequenzen. Für die Bestimmung der Eigenformen wird ein alternativer Messaufbau erarbeitet. Dieser Aufbau nutzt die flache Unterseite einer Brücke, um das ausgesendete Signal auf einen Reflektor auf dem Boden zu spiegeln. Eine permanente Installation von Reflektoren an der Brückenunterseite ist daher nicht erforderlich, wodurch die Anwendung von GBR auf eine große Anzahl von Brücken erweitert wird. Darüber hinaus kann die Messung nicht durch andere Verschiebungskomponenten beeinflusst werden, was das Auftreten von systematischen Abweichungen verringert. Folglich sind die Eigenformen empfindlicher gegenüber Schäden, da die Unsicherheiten reduziert werden. Das zugrunde liegende Prinzip dieses alternativen Messaufbaus wird wiederum durch Vergleiche mit Referenzsensoren validiert

A review of ground-based radar as a noncontact sensor for structural health monitoring of in-field wind turbines blades

Ground-based radar (GBR) are increasingly being used either as a vibration-based or as guided-wave-based structural health monitoring (SHM) sensors for monitoring of wind turbines blades. Despite various studies mentioning the use of radar as transducer for SHM, a singular exclusive review of GBR in blade monitoring may have been lacking. Various studies undertaken for SHM of blades using GBR have largely been laboratory-based or with actual wind turbines in parked positions or focussed on the extraction of only specific condition parameters like frequency or deflection with no validation with actual expected operating data. The present study provides quantitative data that relates in-field monitoring of wind turbines by GBR with actual design operating data. As such it helps the monitoring of blades during design, testing, and operation. Further, it supports the determination of fatigue damage for in-field wind turbine blades especially those made of composite materials by way of condition parameters residuals and deflection. A review of the two GBR-SHM approaches is thus undertaken. Additionally, a case study demonstrating its practical use as a vibration-based noncontact SHM sensors is also provided. The study contributes to the monitoring of blades during design, testing, and operation. Further, it supports the determination of damage detection for in-field wind turbine blades within a 3-tier SHM framework especially those made of composite materials by way of condition parameter residuals of extracted modal frequencies and deflection. © 2018 John Wiley & Sons, Ltd

Passive Wireless Vibration Sensing for Measuring Aerospace Structural Flutter

To reduce energy consumption, emissions, and noise, NASA is exploring the use of high aspect ratio wings on subsonic aircraft. Because high aspect ratio wings are susceptible to flutter events, NASA is also investigating methods of flutter detection and suppression. In support of that work a new remote, non-contact method for measuring flutter-induced vibrations has been developed. The new sensing scheme utilizes a microwave reflectometer to monitor the reflected response from an aeroelastic structure to ultimately characterize structural vibrations. To demonstrate the ability of microwaves to detect flutter vibrations, a carbon fiber-reinforced polymer (CFRP) composite panel was vibrated at various frequencies from 1Hz to 130Hz. The reflectometer response was found to closely resemble the sinusoidal response as measured with an accelerometer up to 100 Hz. The data presented demonstrate that microwaves can be used to measure flutter-induced aircraft vibrations

Contactless Deformation Monitoring of Bridges with Spatio-Temporal Resolution: Profile Scanning and Microwave Interferometry

Against the background of an aging infrastructure, the condition assessment process of existing bridges is becoming an ever more challenging task for structural engineers. Short-term measurements and structural monitoring are valuable tools that can lead to a more accurate assessment of the remaining service life of structures. In this context, contactless sensors have great potential, as a wide range of applications can already be covered with relatively little effort and without having to interrupt traffic. In particular, profile scanning and microwave interferometry, have become increasingly important in the research field of bridge measurement and monitoring in recent years. In contrast to other contactless displacement sensors, both technologies enable a spatially distributed detection of absolute structural displacements. In addition, their high sampling rate enables the detection of the dynamic structural behaviour. This paper analyses the two sensor types in detail and discusses their advantages and disadvantages for the deformation monitoring of bridges. It focuses on a conceptual comparison between the two technologies and then discusses the main challenges related to their application in real-world structures in operation, highlighting the respective limitations of both sensors. The findings are illustrated with measurement results at a railway bridge in operation