NDLI: A novel auto regression and fuzzy-neural combination method to identify cardiovascular dynamics

Content Provider	IEEE Xplore Digital Library
Author	Jingyu Liu Mo Jamshidi Pourbabak, S.
Copyright Year	2004
Description	Author affiliation: Department of Internal Medicine, University of Massachusetts, Worcester, MA 01655 USA (Pourbabak, S.) \|\| University of New Mexico, Center for Autonomous Control Engineering (ACE) And Department of Electrical and Computer Engineering, Albuquerque, NM 87131 USA (Jingyu Liu; Mo Jamshidi)
Abstract	In this paper cardiovascular dynamics, which refers to the dynamic relationship among the heart rate (HR), arterial blood pressure (ABP) and instantaneous lung volume (ILV), is identified through a novel combination approach that consists of a set of linear auto-regression (AR) equations and nonlinear fuzzy-neural inference. Based on linear assumption of cardiovascular system, auto-regressive and moving average method (ARMA) has been popular approaches to identify the complex cardio-system in recent years. Fuzzy set theory is very suitable to systems with uncertainties such as the cardiovascular dynamic system with expert knowledge. Fuzzy- Neural inference paradigm imports the auto-learning property into fuzzy logic engine, therefore extracts some knowledge from data automatically. An effective hybrid approach, which has parallel modular structure of AR and Fuzzy-neural inference, becomes feasible IO interpret physiologically linear component of heart function and nonlinear nervous regulation component respectively. Details of proposed combination method as well as subjects' study results are presented in this paper.
Starting Page	31
Ending Page	38
File Size	650377
Page Count	8
File Format	PDF
ISBN	1889335215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-28
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	TSI Press
Subject Keyword	Cardiology Heart rate Nonlinear dynamical systems Cardiovascular system Arterial blood pressure Uncertainty Signal analysis Frequency domain analysis Lungs Data mining Bio-medical systems ARMA AR Fuzzy-Neural inference cardiovascular dynamics system identification (ID)
Content Type	Text
Resource Type	Article

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