Key result
A mathematical method using the stochasticity of pacing cycles (noise) was developed to determine approximate models of cardiac cell dynamics and detect bifurcations to alternans.
The study presents a novel mathematical method using pacing cycle noise to model cardiac cell dynamics and detect alternans bifurcations.
Hypothesis-generating for alternans-based arrhythmia prediction; requires validation before clinical translation.
Variation in cardiac pacing cycles, as seen, for example, in heart rate variability, has been observed for decades. Contemporarily, various mathematical models have been constructed to investigate the electrical activity of paced cardiac cells. Yet there has not been a study of these cardiac models when there is variation in the pacing cycles such as noise. We present a method that uses the stochasticity of pacing cycles to determine approximate models of the dynamics of cardiac cells, and use these models to detect bifurcations to alternans.
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Dai et al. (2012) studied Cardiac cell dynamics and alternans. Stochasticity of pacing cycles (noise) was evaluated on Determination of approximate models of cardiac cell dynamics and detection of bifurcations to alternans. A mathematical method using the stochasticity of pacing cycles (noise) was developed to determine approximate models of cardiac cell dynamics and detect bifurcations to alternans.
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