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Microvolt T-wave alternans is thought to predict the risk of ventricular arrhythmias in patients with heart disease, although recent clinical studies have conflicting results. Understanding the cellular basis for alternans may not only inform more effective utilisation of the clinical test, but also provide new insights into the causes of lethal arrhythmias in man. Cellular repolarisation alternans is thought to underlie T-wave alternans and in recent years, the concept of discordant repolarisation alternans has emerged as a new paradigm for the induction of re-entrant ventricular arrhythmia. This experimental observation has not been examined in clinically relevant models of pathology and so the aim of this study was to investigate whether increased transmural heterogeneity of repolarisation as a result of heart failure following myocardial infarction in the rabbit would predispose to the development of arrhythmogenic discordant alternans. A rabbit ventricular wedge preparation was developed and the transmural electrophysiology of intact rabbit ventricle was characterised using optical imaging techniques. This revealed transmural gradients of repolarisation in intact rabbit myocardium, which appeared to be influenced by electrotonic load, rather than purely being a reflection of intrinsic cellular differences. Interestingly, repolarisation alternans also appeared in transmural patterns, which were also modified by activation sequence, underlining the role of conduction and electrotonic influences in dictating the spatial patterns of alternans, which may be crucial in determining spatially discordant alternans. In this study, similar baseline electrophysiological characteristics were apparent in the remodelled myocardium of failing hearts compared with normal hearts, underlining the possible importance of dynamic factors in producing the increased vulnerability to re-entrant arrhythmias observed in failing hearts. Repolarisation alternans, elicited by low temperature and rapid pacing, occurred at lower heart rates in failing hearts. At physiological temperature, repolarisation alternans was also more common in failing hearts. Spatially discordant alternans was not consistently observed on the transmural surface and did not appear to be directly related to the development of arrhythmia. Failing hearts displayed an increased vulnerability to ventricular arrhythmia. Although heart failure was associated with both alternans and ventricular arrhythmia, there was no demonstrable mechanistic link between alternans and ventricular arrhythmias in failing hearts. These data establish the occurrence of repolarisation alternans in a clinically relevant pathology, and so constitute an important step forward in our understanding of the experimental paradigm. However, a definitive mechanistic link between alternans and arrhythmia in heart failure is yet to be shown.

There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data.

In the modern clinical and healthcare setting, the electronic collection and analysis of patient related vital signs and parameters are a fundamental part of the relevant treatment plan and positive patient response. Modern analytical techniques combined with readily available computer software today allow for the near real time analysis of digitally acquired measurements. In the clinical context, this can directly relate to patient survival rates and treatment success. The processing of clinical parameters, especially the Electrocardiogram (ECG) in the critical care setting has changed little in recent years and the analytical processes have mostly been managed by highly trained and experienced cardiac specialists. Warning, detection and measurement techniques are focused on the post processing of events relying heavily on averaging and analogue filtering to accurately capture waveform morphologies and deviations. This Ph. D. research investigates an alternative and the possibility to analyse, in the digital domain, bio signals with a focus on the ECG to determine if the feasibility of bit by bit or near real time analysis is indeed possible but more so if the data captured has any significance in the analysis and presentation of the wave patterns in a patient monitoring environment. The research and experiments have shown the potential for the development of logical models that address both the detection and short term predication of possible follow-on events with a focus on Myocardial Ischemic (MI) and Infraction based deviations. The research has shown that real time waveform processing compared to traditional graph based analysis, is both accurate and has the potential to be of benefit to the clinician by detecting deviations and morphologies in a real time domain. This is a significant step forward and has the potential to embed years of clinical experience into the measurement processes of clinical devices, in real terms. Also, providing expert analytical and identification input electronically at the patient bedside. The global human population is testing the healthcare systems and care capabilities with the shortage of clinical and healthcare providers in ever decreasing coverage of treatment that can be provided. The research is a moderate step in further realizing this and aiding the caregiver by providing true and relevant information and data, which assists in the clinical decision process and ultimately improving the required standard of patient care.