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Quantitative Biosciences Thesis Proposal
Lynn H. Jin
School of Physics
Advisor: Dr. Flavio H. Fenton (School of Physics)
Open to the Community
Reaction-Diffusion and Cardiac modeling with applications to defibrillation
Friday, October 14, 2022, at 11:00 am
In Person Location: Howey S107
Zoom Link: https://gatech.zoom.us/j/5447400252?pwd=UmVUWVdnRG01U1N4ZUJ0UHBmcFkyZz09
Committee Members:
Dr. Peter Yunker (School of Physics)
Dr. Elizabeth M. Cherry (School of Computational Science and Engineering)
Dr. Alessandro Loppini (Università Campus Bio-Medico di Roma)
Abstract:
Heart disease is the leading cause of mortality in the US and while there exist many treatments to aid cardiovascular problems, there is ample room for improvement. Computational studies can help in testing and developing new methodologies to treat and perhaps prevent cardiac arrythmias. This thesis consists of three objectives aimed at improving modeling of biological systems, such as cardiac dynamics, and to investigate a new defibrillation methodology.
First, as an introduction to cardiac modeling I investigate fractional diffusion as an alternative to modeling the diffusion of voltage in cardiac tissue. With this we study the reproducibility of experimentally measured spatial alternans and length scales in cardiac tissue, using two common models of cardiac dynamics, the Fenton-Karma model and the Beeler-Reuter model.
Second, as an introduction to high performance computing of biological systems in parallel architectures using the latest technology of Graphic Processing Units (GPUs). I will use WebGL (a JavaScript application programming interface for rendering interactive 2D and 3D graphics within any compatible web browser without the use of plug-ins) which can be used to solve fast and interactively, systems of reaction diffusion equations. I will develop WebGL codes for a large and diverse set of two variable models of biological systems.
Finally, with the knowledge obtained from the first two objectives I will proceed to develop WebGL programs to investigate improvements to low energy antifibrillation pacing (LEAP) techniques.
