Cardiovascular mortality continues to be the leading cause of death in the United Kingdom, China and the United States. Many of these deaths occur suddenly, called sudden cardiac death (SCD), with the number of these events estimated from these three Countries to be over 1,500,000 annually. In the vast majority of documented cases, the SCD is directly caused by ventricular tachycardia (V1). Prediction of the presence of the VT is of great importance. It has been found by using signal averaging (SA) techniques that the appearance of micro signals, called ventricular late potentials (VLPs), is highly correlated with the appearance of VT or SCD. The VLPs are about 0.1% - 1% of the size of the normal ECG in most patients and are masked by various noise sources, so that they can not be seen from the standard electrocardiogram (ECG). The SA techniques, depending largly on averaging many beats, can only detect the microvolt signals that are strictly constant in duration, morphology and timing relative to the QRS complex amongst the considerable amounts of noise which are present The main disadvantage of the technique is that it cannot offer information from an individual beat, i.e. variations among the beats and individual beat information are lost when averaging. This information can be very important in the diagnosis of the development of many heart abnormalities, particularly arrhythmias. This thesis describes various techniques that have been developed for a real-time processing system, in which the system can detect VLPs at the body surface with beat-to-beat variations. One of the most important techniques is the use of adaptive filters to reduce the most disruptive noise -random noise. Clinical investigations have been carried out based on 14 normal and 20 abnormal pathological subjects to produce reproducible results on the developed system. The results show that the system can produce much more information than SA techniques for the prediction of VT.

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The overwhelming prevalence of cardiac related deaths is the motivation behind this thesis to develop body centric antennas for wireless cardiac monitoring. Cardiac monitoring can diagnose a number of conditions including: arrhythmia, ischemia, premature atrial complexes, abnormal sinus rhythms, heart blocks, atrial fibrillation, and more. A body centric antenna operating within the ISM band (2.4-2.48GHz) has been designed, simulated, and tested. The simulation and testing indicate low mutual coupling between antennas of varying distances has been achieved. In addition, the simulation and testing indicate that a thin layer of skin over the test subject further reduces mutual coupling.

The intent of this thesis is to lay groundwork for examining the relationship between seismocardiography (SCG) and phonocardiography (PCG). Both are methods of measuring and describing heart mechanical function. SCG is described as chest vibrations while the heart beats, and PCG is described as acoustic chest surface signal believed to represent the heart valves opening or closing. SCG and PCG have both been used separately in clinical and research settings, but there is currently no clear comparison between the two. Therefore, there has been no way at the present to understand how one signal might inform the other. This study is an effort to fill that gap. SCG and PCG sensors were placed on subjects’ chests while sensor output was simultaneously recorded. The magnitudes of the signals and their trends were then compared against each other to see their similarities and differences. The comparisons demonstrated similar trends between the two sensor types, supporting the hypothesis that there is a relationship between the two that requires further research and insight.

In this thesis, a novel graphene (GN) based electrocardiogram (ECG) sensor is designed, constructed and tested to validate the concept of coating GN, which is a highly electrically conductive material, on Ag substrates of conventional electrodes. The background theory, design, experiments and results for the proposed GN-based ECG sensor are also presented. Due to the attractive electrical and physical characteristics of graphene, a new ECG sensor was investigated by coating GN onto itself. The main focus of this project was to examine the effect of GN on ECG monitoring and to compare its performance with conventional methods. A thorough investigation into GN synthesis on Ag substrate was conducted, which was accompanied by extensive simulation and experimentation. A GN-enabled ECG electrode was characterised by Raman spectroscopy, scanning electron microscopy along with electrical resistivity and conductivity measurements. The results obtained from the GN characteristic experimentation on Raman spectroscopy, detected a 2D peak in the GN-coated electrode, which was not observed with the conventional Ag/AgCl electrode. SEM characterisation also revealed that a GN coating smooths the surface of the electrode and hence, improves the skin-to-electrode contact. Furthermore, a comparison regarding the electrical conductivity calculation was made between the proposed GN-coated electrodes and conventional Ag/AgCl ones. The resistance values obtained were 212.4 Ω and 28.3 Ω for bare and GN-coated electrodes, respectively. That indicates that the electrical conductivity of GN-based electrodes is superior and hence, it is concluded that skin-electrode contact impedance can be lowered by their usage. Additional COMSOL simulation was carried out to observe the effect of an electrical field and surface charge density using GN-coated and conventional Ag/AgCl electrodes on a simplified human skin model. The results demonstrated the effectiveness of the addition of electrical field and surface charge capabilities and hence, coating GN on Ag substrates was validated through this simulation. This novel ECG electrode was tested with various types of electrodes on ten different subjects in order to analyse the obtained ECG signals. The experimental results clearly showed that the proposed GN-based electrode exhibits the best performance in terms of ECG signal quality, detection of critical waves of ECG morphology (P-wave, QRS complex and T-wave), signal-to-noise ratio (SNR) with 27.0 dB and skin-electrode contact impedance (65.82 kΩ at 20 Hz) when compared to those obtained by conventional a Ag/AgCl electrode. Moreover, this proposed GN-based ECG sensor was integrated with core body temperature (CBT) sensor in an ear-based device, which was designed and printed using 3D technology. Subsequently, a finger clipped photoplethysmography (PPG) sensor was integrated with the two-sensors in an Arduino based data acquisition system, which was placed on the subject's arm to enable a wearable multiple physiological measurement system. The physiological information of ECG and CBT was obtained from the ear of the subject, whilst the PPG signal was acquired from the finger. Furthermore, this multiple physiological signal was wirelessly transmitted to the smartphone to achieve continuous and real-time monitoring of physiological signals (ECG, CBT and PPG) on a dedicated app developed using the Java programming language. The proposed system has plenty of room for performance improvement and future development will make it adaptabadaptable, hence being more convenient for the users to implement other applications than at present.

Non-invasive remote detection of cardiac and blood displacements is an important topic in cardiac telemedicine. Here we propose kinocardiography (KCG), a non-invasive technique based onmeasurement of body vibrations produced by myocardial contraction and blood flow through thecardiac chambers and major vessels. KCG is based on ballistocardiography and seismocardiographyand measures 12 degrees-of-freedom (DOF) of body motion. The integral of kinetic energy (iK)and maximum Power (Pmax) obtained from the linear and rotational SCG/BCG signals, was computedover the cardiac cycle, and used as a marker of cardiac mechanical function. We showedthat KCG metrics show high repeatability, can be computed on 50 Hz and 1 kHz SCG/BCG signalsindifferently, that most of the metrics were highly similar when computed on different sensors,and with less than 5% of error when computed on record length longer than 60 s. Finally, weshow that KCG metrics allow detecting dobutamine-induced haemodynamic changes with a highaccuracy and present a major improvement over single axis ballistocardiography or seismocardiography.These results suggest that KCG may be a robust and non-invasive method to monitorcardiac inotropic activity. / La détection à distance et non invasive des déplacements cardiaques et sanguins est un sujet important en télémédecine. Nous proposons ici la kinocardiographie (KCG), une technique non invasive basée sur mesure des vibrations corporelles produites par la contraction du myocarde et par le flux sanguin au travers des cavités cardiaques et des principaux vaisseaux sanguins. La KCG est basée sur la balistocardiographie et la seismocardiographie et mesure 12 degrés de liberté (DOF) de mouvement corporel. L'intégrale de l'énergie cinétique (iK) et la puissance maximale (Pmax) obtenue à partir des signaux SCG / BCG linéaire et rotationnel, a été calculée au cours du cycle cardiaque, et sont utilisées comme marqueur de la fonction mécanique cardiaque. Ce travail montre que les métriques KCG sont caractérisées par une répétabilité élevée, peuvent être calculées sur des signaux SCG / BCG à 50 Hz et à 1 kHz indifféremment, que la plupart des métriques étaient très similaires lorsqu'elles étaient calculées sur différents capteurs, et avec moins de 5% d'erreur lors du calcul sur une longueur d'enregistrement supérieure à 60 s. Enfin ce travail montre que les métriques KCG permettent de détecter les changements hémodynamiques induits par la dobutamine avec précision et présentent une amélioration majeure par rapport à la balistocardiographie à un seul axe ou à la seismocardiographie. Ces résultats suggèrent que la KCG peut être une méthode robuste et non invasive pour surveiller l'activité inotrope du coeur. / Doctorat en Sciences de l'ingénieur et technologie / La défense publique a eu lieu le 05/05/2021. Cet upload remplace l'upload pécédent et contient les derniers commentaires du jury après la défense publique. / info:eu-repo/semantics/nonPublished

Seismocardiography (SCG) is the low frequency chest surface vibration generated by the mechanical activities of the heart. SCG has been found to have clinical utilities in diagnosis of different cardiac diseases. The first part of this study focused on the application of SCG signal in predicting hospital readmissions of the heart failure (HF) patients. Conventional machine learning and deep learning models have been developed using SCG signal acquired from the HF patients. Early HF readmissions was predicted with decent accuracies with these models. This may potentially help the clinicians to identify the patients who need special care and treatment and make timely targeted interventions. This will ensure better management of HF patients and reduce the mortality rate. One of the limitations of using SCG signal in clinical settings is its variability. To investigate SCG variability, an exercise protocol has been developed. SCG signal was acquired from the healthy subjects when they underwent the protocol. It was found that cardiopulmonary interactions may contribute to the variability in SCG signal. The study results help to better understand the source of variability which eventually may increase the clinical utility of SCG signal. Another limitation of SCG signal is that it is highly sensitive to the ambient and locomotion-induced noises. This can distort the SCG signal. Hence, removal of noises is a necessary step to use SCG in ambulatory assessment of HF patients. To encounter this problem, a healthy subject performed different maneuvers to induce few common types of noises in the SCG signal. Different signal processing techniques have been employed to remove the noises from the signal. A comparison among different techniques has been provided which may lead to developing an algorithm in the future that is capable of autodetecting noises and suppress them.

Cardiac time intervals (CTIs) are vital indicators of cardiac health and can be estimated using a combination of electrocardiography (ECG) and seismocardiography (SCG). This study investigates the impact of SCG sensor location across the sternum on CTI estimations and heart rate variability parameters. Signal processing algorithms were developed to detect the opening and closure of heart valves on SCG for CTI calculation. A novel ECG-independent method was also developed based on template matching to determine similar parameters solely based on SCG. Comparative analysis with gold-standard methods were conducted on the SCG fiducial points, evaluating accuracy and performance. Results indicate a high overall average F1 score and correlation for all fiducial point detections. The p values revealed significant differences in SCG-derived CTI estimations across the sensor locations, highlighting the importance of sensor placement for accurate assessments. This finding underscores a fundamental step toward precise evaluation of cardiac health.

Current cardiac monitoring devices are rigid, bulky, and integrate poorly with the human skin, obstructing health monitoring for longer periods. With the miniaturization of electronics, soft and stretchable polymer substrate-based cardiac monitoring device is being developed at Mycronic AB to overcome the aforementioned issues and replacing the traditional rigid electronics-based cardiac monitoring devices. Manufacturing of stretchable cardiac monitoring device includes new materials and manufacturing techniques as well as different end-of-life treatments. The sustainability of this kind of stretchable device is often enquired by curious customers and environment enthusiasts. Without a comprehensive scientific study on the environmental performance of this device, it is difficult for the manufacturer to answer such inquiries. Hence, this study aims to carry out a comparative Life Cycle Assessment (LCA) of rigid and stretchable cardiac monitoring devices. The LCA for both the devices was based on ISO 14044:2006 standards. The impact assessment method used was ReCiPe 2016 (Hierarchist). The LCA results showed that the stretchable cardiac monitor had significantly lower impacts than its rigid counterpart. Lower usage of Printed Circuit Board (PCB) in the stretchable device was the main reason for its better environmental performance. The PCB was identified as the major environmental hotspot in both the devices. / Nuvarande hjärtövervakningsanordningar är styva, skrymmande och dåligt integrerade med människans hud och hindrar övervakning under längre perioder. Inom ramen för det europeiska forskingsprojektet SINTEC har Mycronic bidragit till att utveckla en ny design och tillverkningsmetod för en mjuk och töjbar polymersubstratbaserad övervakningsanordning för att övervinna de ovan nämnda hindren med de traditionella alternativ. Tillverkning av töjbar hjärtövervakningsanordning inkluderar nya material och tillverkningstekniker som ger en ökad hållbarhet som ofta efterfrågas av nyfikna kunder och miljöentusiaster. Men utan en omfattande vetenskaplig studie om enhetens miljöprestanda är det dock svårt för tillverkaren att besvara sådana frågor, och därför syftar denna studie till att utföra en jämförande livscykelanalys (LCA) av styva och töjbara hjärtövervakningsanordningar. LCA för båda enheterna baseras på ISO 14044: 2006-standarder. Den konsekvensbedömning som användes var ReCiPe 2016 (Hierarchist). LCA-resultaten visade att den töjbara hjärtmonitorn hade signifikant lägre påverkan än dess styva motsvarighet. Lägre användning av kretskort (PCB) i den töjbara enheten var den främsta anledningen till dess bättre miljöprestanda och just PCB identifierades som den viktigaste miljöhotspoten i båda enheterna.

Mikroprozessorgesteuerte Implantate haben sich in zahlreichen Bereichen der Medizin etabliert. Physiologische, korpereigene Parameter werden erfasst, abgespeichert und konnen durch Telemetriesysteme weitergeleitet werden. Zusatzlich stehen Therapieoptionen zur Verfugung. Dazu zahlen Neurostimulatoren, welche im Bereich der Schmerztherapie und des fortgeschrittenen Morbus Parkinson erfolgreich angewendet werden ebenso wie Systeme zur Medikamentenapplikation. Beispielhaft hat sich die Entwicklung aktiver Implantate jedoch im Bereich der Herzschrittmacher- und Defibrillatortherapie vollzogen. Die vorliegende Arbeit beschaftigt sich mit der Erforschung physiologischer kardialer Parameter und ihrer Erfassung mit Hilfe von implantierbaren Sensoren. Dabei werden grundlegende technische Aspekte, die spezielle Sensorik zur Erfassung verschiedener Parameter und die Signalverarbeitung dargestellt. Es werden die bereits heute vielfaltigen Moglichkeiten implantierbarer kardialer Monitoringsysteme diskutiert. Neue Moglichkeiten wie das Monitoring ischamischer Ereignisse werden eroffnet. / Mikroprocessor controlled implantable systems are standard in many medical specialities. Physiological parameters can be recorded, stored and transfered via telemetry systems. In addition different therapeutic options are available: neurostimulation to treat patients with refractory pain and morbus parkinson, drug pumps for infusion of insulin etc.. Cardiac pacemakers and implantable cardioverter defibrillators were the driving force in the development of implantable sensors. We investigated different physiological cardiac parameters via implantable sensors. In this paper we discuss basic technical aspects, sensors, signal conditioning and signal analysis. The spectrum of available implantable sensors is shown. New options like the monitoring of transient myocardial ischemia are presented.