0000000000454976

AUTHOR

Pablo Laguna

showing 2 related works from this author

The transient gravitational-wave sky

2013

Interferometric detectors will very soon give us an unprecedented view of the gravitational-wave sky, and in particular of the explosive and transient Universe. Now is the time to challenge our theoretical understanding of short-duration gravitational-wave signatures from cataclysmic events, their connection to more traditional electromagnetic and particle astrophysics, and the data analysis techniques that will make the observations a reality. This paper summarizes the state of the art, future science opportunities, and current challenges in understanding gravitational-wave transients.

Cosmology and Nongalactic Astrophysics (astro-ph.CO)Physics and Astronomy (miscellaneous)Explosive materialmedia_common.quotation_subjectELECTROMAGNETIC COUNTERPARTSFOS: Physical sciencesGeneral Relativity and Quantum Cosmology (gr-qc)01 natural sciencesGeneral Relativity and Quantum CosmologySPIN-DOWN LIMIT0103 physical sciencesPRESUPERNOVA EVOLUTIONCORE-COLLAPSE010306 general physics010303 astronomy & astrophysicsARMED SPIRAL INSTABILITYmedia_commonHigh Energy Astrophysical Phenomena (astro-ph.HE)Astroparticle physicsPhysicsGAMMA-RAY BURSTSNEUTRINO PAIR ANNIHILATIONGravitational waveAstronomyMASS BLACK-HOLESUniverseBAR-MODE INSTABILITYInterferometrySkyData analysisTransient (oscillation)Astrophysics - High Energy Astrophysical PhenomenaDRIVEN SUPERNOVAgravitational waves neutron stars black holesAstrophysics - Cosmology and Nongalactic AstrophysicsClassical and Quantum Gravity
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A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions during Atrial Fibrillation

2017

Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conc…

medicine.medical_specialtyComputer science0206 medical engineeringAtrial fibrillation (AF)Biomedical EngineeringCardiac activity02 engineering and technology030204 cardiovascular system & hematologyIntracardiac injectionmulti-variate autoregressive (MVAR) modeling03 medical and health sciences0302 clinical medicineHeart Conduction SystemInternal medicineAtrial Fibrillationmultielectrode cathetermedicineHumansComputer SimulationPredictabilityModels Statisticalbusiness.industryBody Surface Potential MappingModels CardiovascularPattern recognitionAtrial fibrillationmedicine.disease020601 biomedical engineeringRandom variateAutoregressive modelData Interpretation Statisticalbipolar electrograms (EGMs)Multivariate AnalysisSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCardiologyGranger causality (GC)Artificial intelligencebusiness
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