The contact electrogram and its architectural determinants in atrial fibrillation

The electrogram is the sine qua non of excitable tissues, yet classification in atrial fibrillation (AF) remains poorly related to substrate factors. The objective of this thesis was to establish the relationship between electrograms and two commonly implicated substrate factors, connexin 43 and fibrosis in AF. The substrates and methods chosen to achieve this ranged from human acutely induced AF using open chest surgical mapping (Chapter 6), ex vivo whole heart Langendorff (Chapter 7) with in vivo telemetry confirming spontaneous AF in a new species of rat, the Brown Norway and finally isolated atrial preparations from an older cohort of rats using orthogonal pacing and novel co-localisation methods at sub-millimetre resolution and in some atria, optical mapping (Chapter 8). In rodents, electrode size and spacing was varied (Chapters 5, 10) to study its effects on structure function correlations (Chapter 9). Novel indices of AF organisation and automated electrogram morphology were used to quantify function (Chapter 4). Key results include the discoveries that humans without any history of prior AF have sinus rhythm electrograms with high spectral frequency content, that wavefront propagation velocities correlated with fibrosis and connexin phosphorylation ratios, that AF heterogeneity of conduction correlates to fibrosis and that orthogonal pacing in heavily fibrosed atria causes anisotropy in electrogram-fibrosis correlations. Furthermore, fibrosis and connexin 43 have differing and distinct spatial resolutions in their relationship with AF organisational indices. In conclusion a new model of AF has been found, and structure function correlations shown on an unprecedented scale, but with caveats of electrode size and direction dependence. These findings impact structure function methods and prove the effect of substrate on AF organisation.Open Acces

Intelligent Biosignal Processing in Wearable and Implantable Sensors

This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

Advances in Electrocardiograms

Electrocardiograms have become one of the most important, and widely used medical tools for diagnosing diseases such as cardiac arrhythmias, conduction disorders, electrolyte imbalances, hypertension, coronary artery disease and myocardial infarction. This book reviews recent advancements in electrocardiography. The four sections of this volume, Cardiac Arrhythmias, Myocardial Infarction, Autonomic Dysregulation and Cardiotoxicology, provide comprehensive reviews of advancements in the clinical applications of electrocardiograms. This book is replete with diagrams, recordings, flow diagrams and algorithms which demonstrate the possible future direction for applying electrocardiography to evaluating the development and progression of cardiac diseases. The chapters in this book describe a number of unique features of electrocardiograms in adult and pediatric patient populations with predilections for cardiac arrhythmias and other electrical abnormalities associated with hypertension, coronary artery disease, myocardial infarction, sleep apnea syndromes, pericarditides, cardiomyopathies and cardiotoxicities, as well as innovative interpretations of electrocardiograms during exercise testing and electrical pacing

Morphological and electrophysiological differences between the Caucasian and South Asian Atrium

Introduction: South Asians (SAs) have a low prevalence of atrial fibrillation (AF) compared with Caucasians despite a higher prevalence of hypertension, diabetes mellitus and coronary artery disease. The aim of this thesis was to determine whether this was related to an under-detection of the arrhythmia and if not, whether differences in left atrial (LA) size, electrophysiological properties or autonomic function in SAs might help to explain this disparity. Methods: Retrospective and prospective cohort studies were performed on SA and Caucasian participants using data from implantable cardiac devices, cardiac magnetic resonance imaging scans, invasive electrophysiology studies and a range of non-invasive cardiac investigations. Results: The cumulative incidence of subclinical AF was significantly lower in SAs compared with Caucasians (log rank p=0.002) with an annual event rate of 6.9% versus 13.9%. In comparison with Caucasians, SAs were of a smaller height with lower lean body mass and higher waist:hip ratio; had lower minimum (27.7±11.1 ml vs 34.9±12.3 ml, p=0.002) and maximum LA volumes (64.7±21.1 ml vs 80.9±22.5 ml, p<0.001) even after matching for body surface area; lower P wave dispersion (males 28.0(12)ms vs 25.0(12)ms, p=0.039; females 24.0(12)ms vs 22.0(12)ms, p=0.004) and P wave terminal force in lead V1 (males 0.031(0.04)mm•s vs 0.021(0.03) mm•s, p=0.023; females 0.036(0.04)mm•s vs 0.034(0.04)mm•s, p=0.030), electrophysiological variations related to the inhomogeneity of LA conduction and LA size respectively; increased heart rate (82.5(18)bpm vs 78.0(18)bpm, p=0.024), lower atrioventricular (280(50)ms vs 300(60)ms, p=0.001) and ventriculoatrial (300(60)ms vs 320(93)ms, p=0.013) effective refractory periods and lower heart rate variability (in SA males), suggestive of sympathetic predominance. Conclusions: SAs have reduced LA size and evidence of increased sympathetic tone and reduced inhomogeneity in LA conduction. The morphological, electrophysiological and autonomic differences identified in SAs may help to explain why this ethnic group has a lower prevalence of AF

Cardiac Arrhythmias

The most intimate mechanisms of cardiac arrhythmias are still quite unknown to scientists. Genetic studies on ionic alterations, the electrocardiographic features of cardiac rhythm and an arsenal of diagnostic tests have done more in the last five years than in all the history of cardiology. Similarly, therapy to prevent or cure such diseases is growing rapidly day by day. In this book the reader will be able to see with brighter light some of these intimate mechanisms of production, as well as cutting-edge therapies to date. Genetic studies, electrophysiological and electrocardiographyc features, ion channel alterations, heart diseases still unknown , and even the relationship between the psychic sphere and the heart have been exposed in this book. It deserves to be read

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems

Analysis of Heart Rate Variability During Focal Parasympathetic Drive of the Rat Baroreflex

Indiana University-Purdue University Indianapolis (IUPUI)Autonomic control of the heart results in variations in the intervals between heart beats, known as heart rate variability. One of the defining components of autonomic control is the baroreflex, a negative feedback controller that balances heart rate and blood pressure. The baroreflex is under constant command from the branches of the autonomic nervous system. To better understand how the autonomic nervous system commands the baroreflex, a baroreflex reflexogenic animal protocol was carried out. Heart rate variability analysis and baroreflex sensitivity were used to quantify the neural control of the heart. This thesis reconfirmed the existence of sexually dimorphic properties in the baroreflex through the use of heart rate variability analysis and baroreflex sensitivity. It was discovered that there are many caveats to utilizing heart rate variability analysis, which have to be addressed both in the experimental protocol and the signal processing technique. Furthermore, it was suggested that the slope method for quantifying baroreflex sensitivity also has many caveats, and that other baroreflex sensitivity methods are likely more optimal for quantifying sustained activation of the baroreflex. By utilizing various heart rate variability signal processing algorithms to assess autonomic tone in Sprague-Dawley rats during rest and sustained electrical activation of the baroreflex, the null hypothesis was rejected

On the Recognition of Emotion from Physiological Data

This work encompasses several objectives, but is primarily concerned with an experiment where 33 participants were shown 32 slides in order to create ‗weakly induced emotions‘. Recordings of the participants‘ physiological state were taken as well as a self report of their emotional state. We then used an assortment of classifiers to predict emotional state from the recorded physiological signals, a process known as Physiological Pattern Recognition (PPR). We investigated techniques for recording, processing and extracting features from six different physiological signals: Electrocardiogram (ECG), Blood Volume Pulse (BVP), Galvanic Skin Response (GSR), Electromyography (EMG), for the corrugator muscle, skin temperature for the finger and respiratory rate. Improvements to the state of PPR emotion detection were made by allowing for 9 different weakly induced emotional states to be detected at nearly 65% accuracy. This is an improvement in the number of states readily detectable. The work presents many investigations into numerical feature extraction from physiological signals and has a chapter dedicated to collating and trialing facial electromyography techniques. There is also a hardware device we created to collect participant self reported emotional states which showed several improvements to experimental procedure

Advanced analyses of physiological signals and their role in Neonatal Intensive Care

Preterm infants admitted to the neonatal intensive care unit (NICU) face an array of life-threatening diseases requiring procedures such as resuscitation and invasive monitoring, and other risks related to exposure to the hospital environment, all of which may have lifelong implications. This thesis examined a range of applications for advanced signal analyses in the NICU, from identifying of physiological patterns associated with neonatal outcomes, to evaluating the impact of certain treatments on physiological variability. Firstly, the thesis examined the potential to identify infants at risk of developing intraventricular haemorrhage, often interrelated with factors leading to preterm birth, mechanical ventilation, hypoxia and prolonged apnoeas. This thesis then characterised the cardiovascular impact of caffeine therapy which is often administered to prevent and treat apnoea of prematurity, finding greater pulse pressure variability and enhanced responsiveness of the autonomic nervous system. Cerebral autoregulation maintains cerebral blood flow despite fluctuations in arterial blood pressure and is an important consideration for preterm infants who are especially vulnerable to brain injury. Using various time and frequency domain correlation techniques, the thesis found acute changes in cerebral autoregulation of preterm infants following caffeine therapy. Nutrition in early life may also affect neurodevelopment and morbidity in later life. This thesis developed models for identifying malnutrition risk using anthropometry and near-infrared interactance features. This thesis has presented a range of ways in which advanced analyses including time series analysis, feature selection and model development can be applied to neonatal intensive care. There is a clear role for such analyses in early detection of clinical outcomes, characterising the effects of relevant treatments or pathologies and identifying infants at risk of later morbidity