Das Tuhin Subhra, Wilson Dan
Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee 37996, USA.
Phys Rev E. 2021 May;103(5-1):052203. doi: 10.1103/PhysRevE.103.052203.
Phase-isostable reduction is an emerging model reduction strategy that can be used to accurately replicate nonlinear behaviors in systems for which standard phase reduction techniques fail. In this work, we derive relationships between the cycle-to-cycle variance of the reduced isostable coordinates for systems subject to both additive white noise and periodic stimulation. Using this information, we propose a data-driven technique for inferring nonlinear terms of the phase-isostable coordinate reduction framework. We apply the proposed model inference strategy to the biologically motivated problem of eliminating cardiac alternans, an arrhythmia that is widely considered to be a precursor to more deadly cardiac arrhythmias. Using this strategy, by simply measuring a series of action potential durations in response to periodic stimulation, we are able to identify energy-optimal, nonfeedback control inputs to stabilize a period-1, alternans-free solution.
相位等稳约简是一种新兴的模型约简策略，可用于准确复制标准相位约简技术失效的系统中的非线性行为。在这项工作中，我们推导了受加性白噪声和周期性刺激的系统的约简等稳坐标的逐周期方差之间的关系。利用这些信息，我们提出了一种数据驱动技术，用于推断相位等稳坐标约简框架的非线性项。我们将所提出的模型推断策略应用于消除心脏交替性心律失常这一具有生物学动机的问题，这种心律失常被广泛认为是更致命心律失常的先兆。使用该策略，通过简单测量一系列响应周期性刺激的动作电位持续时间，我们能够识别出能量最优的非反馈控制输入，以稳定周期为1且无交替性心律失常的解。
