Search results for "Local nonlinear prediction"

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Assessing Causality in normal and impaired short-term cardiovascular regulation via nonlinear prediction methods

2009

We investigated the ability of mutual nonlinear prediction methods to assess causal interactions in short-term cardiovascular variability during normal and impaired conditions. Directional interactions between heart period (RR interval of the ECG) and systolic arterial pressure (SAP) short-term variability series were quantified as the cross-predictability (CP) of one series given the other, and as the predictability improvement (PI) yielded by the inclusion of samples of one series into the prediction of the other series. Nonlinear prediction was performed through global approximation (GA), approximation with locally constant models (LA0) and approximation with locally linear models (LA1) …

Adultmedicine.medical_specialtySupine positionTime FactorsGeneral MathematicsRR intervalGlobal nonlinear predictionGeneral Physics and AstronomyNeurally-mediated syncopeBlood PressureK-nearest neighbours local nonlinear predictionCardiovascular SystemSyncopeCardiovascular Physiological PhenomenaPhysics and Astronomy (all)Engineering (all)Control theoryHeart RateNeurally mediated syncopeInternal medicinemedicinePressureHumansMathematics (all)Computer SimulationOut-of-sample predictionMathematicsModels StatisticalGeneral EngineeringLinear modelModels CardiovascularNonlinear granger causalityModels TheoreticalControl subjectsHeart rate and arterial pressure variabilityCausalityNonlinear predictionTerm (time)Case-Control StudiesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCardiologyAlgorithms
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A method for the time-varying nonlinear prediction of complex nonstationary biomedical signals

2009

A method to perform time-varying (TV) nonlinear prediction of biomedical signals in the presence of nonstationarity is presented in this paper. The method is based on identification of TV autoregressive models through expansion of the TV coefficients onto a set of basis functions and on k -nearest neighbor local linear approximation to perform nonlinear prediction. The approach provides reasonable nonlinear prediction even for TV deterministic chaotic signals, which has been a daunting task to date. Moreover, the method is used in conjunction with a TV surrogate method to provide statistical validation that the presence of nonlinearity is not due to nonstationarity itself. The approach is t…

Time FactorsComputer scienceSpeech recognitionChaoticBiomedical EngineeringBasis functionModels BiologicalSurrogate dataYoung AdultHeart RatePredictive Value of TestsNonstationary signalHumansComputer SimulationEEGPredictabilitySignal processingNonlinear dynamicElectroencephalographySignal Processing Computer-AssistedComplexityLocal nonlinear predictionNonlinear systemNonlinear DynamicsAutoregressive modelData Interpretation StatisticalSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaLinear approximationSurrogate dataAlgorithmHeart rate variability (HRV)Algorithms
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