Assessment of granger causality by nonlinear model identification: Application to short-term cardiovascular variability

Annals of Biomedical Engineering

Volumn 36, Issue 3, 2008, Pages 381-395

  Faes, Luca ^a   Nollo, Giandomenico ^a   Chon, Ki H ^b  

^a UNIVERSITY OF TRENTO   (Italy)

^b St Francis Hospital The Heart Center   (United States)

Author keywords

Arterial pressure variability; Autoregressive exogenous models; Cardiovascular regulation; Directionality; Heart rate variability; Nonlinear parametric models; Optimal parameter search; Surrogate data

Indexed keywords

BLOOD PRESSURE; COMPUTER SIMULATION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; RANDOM PROCESSES; STATISTICAL METHODS;

ARTERIAL PRESSURE VARIABILITY; AUTOREGRESSIVE EXOGENOUS MODELS; CARDIOVASCULAR REGULATION; DIRECTIONALITY; HEART RATE VARIABILITY; NONLINEAR PARAMETRIC MODELS; OPTIMAL PARAMETER SEARCH; SURROGATE DATA;

CARDIOLOGY;

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; BLOOD PRESSURE; COMPUTER SIMULATION; EVALUATION; FEEDBACK SYSTEM; HEART RATE; HUMAN; NONLINEAR SYSTEM; PHYSIOLOGY; REGRESSION ANALYSIS; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ANIMALS; BLOOD PRESSURE; COMPUTER SIMULATION; FEEDBACK; HEART RATE; HUMANS; MODELS, CARDIOVASCULAR; NONLINEAR DYNAMICS; REGRESSION ANALYSIS; SENSITIVITY AND SPECIFICITY;

EID: 39149085335     PISSN: 00906964     EISSN: 15739686     Source Type: Journal    
DOI: 10.1007/s10439-008-9441-z     Document Type: Article

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