Multimodal Pressure Flow Analysis: Application of Hilbert Huang Transform in Cerebral Blood Flow Regulation.

EURASIP Journal on Advances in Signal Processing
Men-Tzung LoV Novak

Abstract

Quantification of nonlinear interactions between two nonstationary signals presents a computational challenge in different research fields, especially for assessments of physiological systems. Traditional approaches that are based on theories of stationary signals cannot resolve nonstationarity-related issues and, thus, cannot reliably assess nonlinear interactions in physiological systems. In this review we discuss a new technique "Multi-Modal Pressure Flow method (MMPF)" that utilizes Hilbert-Huang transformation to quantify dynamic cerebral autoregulation (CA) by studying interaction between nonstationary cerebral blood flow velocity (BFV) and blood pressure (BP). CA is an important mechanism responsible for controlling cerebral blood flow in responses to fluctuations in systemic BP within a few heart-beats. The influence of CA is traditionally assessed from the relationship between the well-pronounced systemic BP and BFV oscillations induced by clinical tests. Reliable noninvasive assessment of dynamic CA, however, remains a challenge in clinical and diagnostic medicine.In this brief review we: 1) present an overview of transfer function analysis (TFA) that is traditionally used to quantify CA; 2) describe the a MMPF method...Continue Reading

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Citations

Nov 5, 2010·Medical & Biological Engineering & Computing·Erik D GommerJos P H Reulen
Sep 1, 2012·Medical & Biological Engineering & Computing·Fuyuan Liao, Yih-Kuen Jan
Jan 18, 2014·Medical & Biological Engineering & Computing·Chia-Chi ChangHung-Yi Hsu
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Mar 18, 2020·Frontiers in Neuroscience·Andres SolerMarta Molinas

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