Cardiac alternans, a beat-to-beat alternation in action potential duration, is a marker of ventricular fibrillation, a fatal heart rhythm that kills hundreds of thousands of people in the United States each year. Mathematically, the propensity of alternans is characterized by an eigenvalue approaching -1. In this project, we will explore and develop data-driven statistical techniques, which are independent of any underlying dynamical model to estimate the dominant eigenvalues and their standard errors from the time series of one or a few measurable quantities, e.g. transmembrane voltages in cardiac experiments.
|Student participants, from left: Vernoica Go, Biochemistry/Statistics, UT-Knoxville; John Shamshoian, Mathematics, California Polytechnic State University; Megan Comer, Chemistry Teacher, Campbell County High School; Rebecca McDowell, Mathematics Teacher, West High School|
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