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My main area of research is the interdisciplinary field of
computational cardiac electrophysiology and arrhythmias.
Essentially, I use computational modeling and simulation
to improve the understanding of cardiac dynamics
in normal and diseased states
and to design advanced strategies for prevention and
treatment of arrhythmias.
Gaining new insights into cardiac electrical dynamics
and the dangerous arrhythmias that can develop in the
heart is an important challenge.
Sudden cardiac death resulting from disruptions to the
heart’s normal rhythm remains the leading cause of death
in the industrialized world,
causing about 20 percent of all deaths.
Research has shown that the most dangerous cardiac
arrhythmias arise from reentrant waves corresponding
to spiral or scroll waves of electrical activity within the heart.
Because the frequencies of these reentrant waves are higher
than the heart's natural pacemaker frequency,
the heart’s normal rhythm is disturbed, triggering
mechanical dysfunction that prevents adequate contraction
and pumping of blood.
Arrhythmias may be more likely to occur when certain
diseases are present, but they can arise even in
individuals with no diagnosed heart disease.
Despite the medical importance, much remains to be
understood about the mechanisms responsible for the
formation and evolution of arrhythmias in human hearts.
Although traditional experiments and clinical work
are necessary, computational and mathematical models of cardiac
electrical processes and numerical simulations of
these models have been used for several decades to
derive new insights into and deeper understanding of
normal and abnormal cardiac cell and tissue behavior.
I am involved in research at the leading edge of several aspects of this area, including advanced computational methods, model development and analysis, and physiological applications of modeling to interpret experimental and clinical observations. New insights from this work have the potential to improve understanding and to lead to better treatment strategies for several types of cardiovascular disease; they also should extend to related physiological systems.
Contact:
School of Computational Science and EngineeringGeorgia Institute of Technology
756 West Peachtree Street Northwest
Suite 1300 South
Atlanta GA 30332-4017
Office: Coda E1346B
Phone: (404) 894-3889
Email: elizabeth.cherry@gatech.edu