Dai Shu, Keener James P
Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio 43210, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jun;85(6 Pt 1):061902. doi: 10.1103/PhysRevE.85.061902. Epub 2012 Jun 1.
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.
心脏起搏周期的变化,例如心率变异性中所见的情况,已经被观察了数十年。当下,已经构建了各种数学模型来研究起搏心脏细胞的电活动。然而,当起搏周期存在诸如噪声之类的变化时,尚未有对这些心脏模型的研究。我们提出了一种方法,该方法利用起搏周期的随机性来确定心脏细胞动力学的近似模型,并使用这些模型来检测向交替性的分岔。