Adaptive Signal Modeling and Feature Extraction Methods for Analyzing Cardiac Fibrillation

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The heart is a fascinating and complexly designed vital organ with electro mechanical functionalities that beats (i.e. expands and contracts) rhythmically to maintain blood circulation throughout the lifetime of a living being. When this rhythm gets disturbed or the heart goes into arrhythmic contractions and expansions for a multitude of pathophysiological reasons, it may result in life threatening medical conditions. These rhythmic disorders can result in cardiac arrhythmias, which can seriously affect cardiac output (or blood flow). Ventricular fibrillation (VF) is an arrhythmia that originates from the lower chambers of the heart and can lead to sudden cardiac death if medical attention is not provided within minutes of onset. Most of the approximately 300,000 sudden cardiac deaths (SCDs) reported every year in North America (45,000 of them in Canada) is related to VF. Atrial Fibrillation (AF), in comparison, originates from the upper chambers of the heart, and although not as lethal as VF, can seriously affect quality of life and increase the risk of stroke in patients. There is a great need to develop new engineering methodologies to improve understanding and assist in reducing the mortality rates associated with these cardiac arrhythmias. The mechanisms behind VF and AF are elusive due to the nonstationary nature of the processes and the ethical/practical limitations in studying human arrhythmias. Over the years, signal processing approaches have aided the medical community in extracting information from electrograms (electrical signals from the heart’s surface) and electrocardiograms (cardiac electrical signals from the body surface), optimizing treatment options, and developing intelligent medical devices. The proposed research program will aim to identify novel ways to quantify these cardiac arrhythmias, so as to arrive at short-term and long-term treatment options. Specifically, the research, in collaboration with Toronto General Hospital and St. Michael’s Hospital, will develop advanced electrogram and electrocardiogram signal and image processing techniques to improve the efficiency of long-term focused medical therapies in identifying and eliminating the sources responsible for these arrhythmias, increase the intelligence of implantable devices, and provide vital information to the emergency medical services personnel to improve survival rates in cardiac resuscitation efforts.