Garzón Alejandro, Grigoriev Roman O, Fenton Flavio H
School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332-0430, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80(2 Pt 1):021932. doi: 10.1103/PhysRevE.80.021932. Epub 2009 Aug 25.
Cardiac alternans, a beat-to-beat alternation of cardiac electrical dynamics, and ventricular tachycardia, generally associated with a spiral wave of electrical activity, have been identified as frequent precursors of the life-threatening spatiotemporally chaotic electrical state of ventricular fibrillation (VF). Schemes for the elimination of alternans and the stabilization of spiral waves through the injection of weak external currents have been proposed as methods to prevent VF but have not performed at the level required for clinical implementation. In this paper we propose a control method based on linear-quadratic regulator (LQR) control. Unlike most previously proposed approaches, our method incorporates information from the underlying model to increase efficiency. We use a one-dimensional ringlike geometry, with a single control electrode, to compare the performance of our method with that of two other approaches, quasi-instantaneous suppression of unstable modes (QISUM) and time-delay autosynchronization (TDAS). We find that QISUM fails to suppress alternans due to conduction block. Although both TDAS and LQR succeed in suppressing alternans, LQR is able to suppress the alternans faster and using a much weaker control current. Our results highlight the benefits of a model-based control approach despite its inherent complexity compared with nonmodel-based control such as TDAS.
心脏交替现象,即心脏电动力学的逐搏交替,以及通常与电活动螺旋波相关的室性心动过速,已被确定为危及生命的室颤(VF)时空混沌电状态的常见先兆。通过注入微弱外部电流来消除交替现象和稳定螺旋波的方案已被提出作为预防室颤的方法,但尚未达到临床应用所需的水平。在本文中,我们提出了一种基于线性二次调节器(LQR)控制的方法。与大多数先前提出的方法不同,我们的方法结合了基础模型的信息以提高效率。我们使用具有单个控制电极的一维环形几何结构,将我们的方法与其他两种方法,即不稳定模式的准瞬时抑制(QISUM)和时延自同步(TDAS)的性能进行比较。我们发现,由于传导阻滞,QISUM无法抑制交替现象。虽然TDAS和LQR都成功抑制了交替现象,但LQR能够更快地抑制交替现象,并且使用的控制电流要弱得多。我们的结果突出了基于模型的控制方法的优势,尽管与诸如TDAS等非基于模型的控制相比,其具有内在的复杂性。