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This work addresses major challenges of heart model personalization. Analysis techniques for clinical intracardiac electrograms determine wave direction and conduction velocity from single beats. Electrophysiological measurements are simulated to validate the models. Uncertainties in tissue conductivities impact on simulated ECGs. A minimal model of cardiac myocytes is adapted to the atria. This makes personalized cardiac models a promising technique to improve treatment of atrial arrhythmias.
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With upwards of 4.5 million deaths worldwide each year, and more than one tenth of these occurring in those with no previously documented heart disease, sudden arrhythmic death (SAD) is both a major public health burden and a highly emotive issue for society at large. Recent years have witnessed a marked expansion in our knowledge of the physiology underlying SAD, both in the context of hereditary and acquired cardiac disorders. Thanks largely to work in genetically modified animals, the growth in our understanding of mechanisms underlying arrhythmia in the hereditary channelopathies has been particularly marked. Our growing knowledge of the fundamental mechanisms underlying SAD has so far failed to spur substantial developments in clinical practice. Despite a large body of work in both humans and animals, it remains impossible to confidently identify those at high risk of SAD, making pre-emptive therapy a challenge. What is more, with the thankful exception of the implantable cardioverter-defibrillators and pharmacological agents in very specific situations, there has been depressingly little progress in finding new and effective therapies. This Research Topic aims to go some way towards bridging the gap between advances in basic science and the development and delivery of new therapies. It brings together original research contributions and review articles from key opinion leaders in the field, focusing on the direct clinical implications of the basic science research now and in the future.
sudden death --- ventricular arrhythmia --- ventricular tachycardia --- Ventricular Fibrillation --- Atrial Fibrillation --- arrhythmia mechanisms --- Brugada Syndrome --- Inherited arrhythmia syndromes --- Channelopathies --- cardiac modelling
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This open access volume presents a novel computational framework for understanding how collections of excitable cells work. The key approach in the text is to model excitable tissue by representing the individual cells constituting the tissue. This is in stark contrast to the common approach where homogenization is used to develop models where the cells are not explicitly present. The approach allows for very detailed analysis of small collections of excitable cells, but computational challenges limit the applicability in the presence of large collections of cells.
Mathematical and Computational Biology --- Applications of Mathematics --- Mathematical Modeling and Industrial Mathematics --- applied mathematics --- scientific computing --- computational physiology --- finite element methods --- cardiac modelling --- biomechanics --- numerical methods --- preconditioning --- open access --- Maths for scientists --- Mathematical modelling --- Maths for engineers
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