Intrinsic frequency for a systems approach to haemodynamic waveform analysis with clinical applications

Author:

Pahlevan Niema M.1,Tavallali Peyman2,Rinderknecht Derek G.3,Petrasek Danny4,Matthews Ray V.5,Hou Thomas Y.2,Gharib Morteza3

Affiliation:

1. Medical Engineering, Division of Engineering and Applied Sciences, California Institute of Technology, 1200 East California Boulevard, MC 301-46, Pasadena, CA 91125, USA

2. 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

3. Graduate Aerospace Laboratories, Division of Engineering and Applied Sciences, California Institute of Technology, 1200 East California Boulevard, MC 205-45, Pasadena, CA 91125, USA

4. Medical Engineering, Division of Engineering and Applied Sciences, California Institute of Technology, 1200 East California Boulevard, MC 217-50, Pasadena, CA 91125, USA

5. Keck School of Medicine, University of Southern California, 1510 San Pablo Street, Suite 322, Los Angeles, CA 90033, USA

Abstract

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; ω 1 and ω 2 ). 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 ( ω 1 = ω 2 ). Extracted IFs from clinical data indicate that at young ages the total frequency variation (Δ ω = ω 1ω 2 ) is close to zero and that Δ ω 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.

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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