Pahlevan Niema M, Tavallali Peyman, Rinderknecht Derek G, Petrasek Danny, Matthews Ray V, Hou Thomas Y, Gharib Morteza
Medical Engineering, Division of Engineering and Applied Sciences, California Institute of Technology, 1200 East California Boulevard, MC 301-46, Pasadena, CA 91125, USA.
Applied and Computational Mathematics, Division of Engineering and Applied Sciences, California Institute of Technology, 1200 East California Boulevard, MC 9-94, Pasadena, CA 91125, USA.
J R Soc Interface. 2014 Sep 6;11(98):20140617. doi: 10.1098/rsif.2014.0617.
The reductionist approach has dominated the fields of biology and medicine for nearly a century. Here, we present a systems science approach to the analysis of physiological waveforms in the context of a specific case, cardiovascular physiology. Our goal in this study is to introduce a methodology that allows for novel insight into cardiovascular physiology and to show proof of concept for a new index for the evaluation of the cardiovascular system through pressure wave analysis. This methodology uses a modified version of sparse time-frequency representation (STFR) to extract two dominant frequencies we refer to as intrinsic frequencies (IFs; ω1 and ω2). The IFs are the dominant frequencies of the instantaneous frequency of the coupled heart + aorta system before the closure of the aortic valve and the decoupled aorta after valve closure. In this study, we extract the IFs from a series of aortic pressure waves obtained from both clinical data and a computational model. Our results demonstrate that at the heart rate at which the left ventricular pulsatile workload is minimized the two IFs are equal (ω1 = ω2). Extracted IFs from clinical data indicate that at young ages the total frequency variation (Δω = ω1 - ω2) is close to zero and that Δω increases with age or disease (e.g. heart failure and hypertension). While the focus of this paper is the cardiovascular system, this approach can easily be extended to other physiological systems or any biological signal.
近一个世纪以来,还原论方法在生物学和医学领域占据主导地位。在此,我们提出一种系统科学方法,用于在心血管生理学这一特定案例的背景下分析生理波形。我们在本研究中的目标是引入一种方法,以便对心血管生理学有全新的见解,并通过压力波分析展示一种用于评估心血管系统的新指标的概念验证。该方法使用稀疏时频表示(STFR)的改进版本来提取两个主导频率,我们将其称为固有频率(IFs;ω1和ω2)。IFs是主动脉瓣关闭前心脏 + 主动脉耦合系统的瞬时频率以及瓣膜关闭后解耦的主动脉的主导频率。在本研究中,我们从临床数据和计算模型获得的一系列主动脉压力波中提取IFs。我们的结果表明,在左心室搏动负荷最小化的心率下,两个IFs相等(ω1 = ω2)。从临床数据中提取的IFs表明,在年轻时,总频率变化(Δω = ω1 - ω2)接近零,并且Δω随年龄或疾病(如心力衰竭和高血压)增加。虽然本文的重点是心血管系统,但这种方法可以轻松扩展到其他生理系统或任何生物信号。