0000000000466244

AUTHOR

Daniele Orrico

showing 2 related works from this author

An identifiable model to assess frequency-domain Granger causality in the presence of significant instantaneous interactions

2010

We present a new approach for the investigation of Granger causality in the frequency domain by means of the partial directed coherence (PDC). The approach is based on the utilization of an extended multivariate autoregressive (MVAR) model, including instantaneous effects in addition to the lagged effects traditionally studied, to fit the observed multiple time series prior to PDC computation. Model identification is performed combining standard MVAR coefficient estimation with a recent technique for instantaneous causal modeling based on independent component analysis. The approach is first validated on simulated MVAR processes showing that, in the presence of instantaneous effects, only t…

System identificationBiomedical EngineeringReproducibility of ResultsElectroencephalographyIndependent component analysisSensitivity and SpecificityPattern Recognition AutomatedAutoregressive modelGranger causalityArtificial IntelligenceFrequency domainStatisticsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaEconometricsCoherence (signal processing)HumansDiagnosis Computer-AssistedTime seriesAlgorithmsMathematicsCausal model
researchProduct

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation

2011

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15. Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or …

AdultMaleComputer sciencePhotic StimulationBiomedical EngineeringBiophysicsElectroencephalographyEyeMachine learningcomputer.software_genreBrain IschemiaYoung AdultIschemiamedicineHumansEEGPredictabilityIntermittent photic stimulationK nearest neighbourPredictability mapAgedScalpLocal linearmedicine.diagnostic_testbusiness.industrySpectrum AnalysisLocal linear predictionElectroencephalographySignal Processing Computer-AssistedPattern recognitionScalp eegmedicine.anatomical_structureScalpSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCortexLinear ModelsFemaleArtificial intelligencebusinesscomputerPhotic StimulationMedical Engineering & Physics
researchProduct