Stochastic Petri net modeling of wave sequences in cardiac arrhythmias.
We describe a methodology for modeling heart rhythms observed in electrocardiograms. In particular, we present a procedure to derive simple dynamic models that capture the cardiac mechanisms which control the particular timing sequences of P and R waves characteristic of different arrhythmias. By treating the cardiac electrophysiology at an aggregate level, simple network models of the wave generating system under a variety of diseased conditions can be developed. These network models are then systematically converted to stochastic Petri nets which offer a compact mathematical framework to express the dynamics and statistical variability of the wave generating mechanisms. Models of several arrhythmias are included in order to illustrate the methodology.
Chin
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TM
Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge 02139.
Willsky
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AS
D001145:Arrhythmias, Cardiac / Q000503:physiopathology*; D004562:Electrocardiography; D006329:Heart Conduction System / Q000503:physiopathology*; D006801:Humans; D008955:Models, Cardiovascular; D013269:Stochastic Processes