Search results for "Body surface potential map"

showing 4 items of 14 documents

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

2017

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…

TachycardiaPhysiologyComputer sciencemedicine.medical_treatment02 engineering and technology030204 cardiovascular system & hematologyBioinformaticsBiochemistryACTIVATIONElectrocardiography0302 clinical medicineHeart RateAtrial FibrillationMedicine and Health SciencesImage Processing Computer-AssistedDEPOLARIZATIONBody surface P-wave integral mapsCardiac AtriaAtrial ectopic beatsMultidisciplinarymedicine.diagnostic_testORIGINApplied MathematicsSimulation and ModelingP waveBody Surface Potential MappingQRHeartHUMANSaarhythmiasAblationANATOMYBioassays and Physiological Analysismachine learningPhysical SciencesAtrial ectopic beatsMedicineAtrial Premature ComplexesFIBRILLATIONmedicine.symptomTACHYCARDIAAlgorithmsResearch ArticleclusteringTachycardia Ectopic AtrialComputer and Information SciencesSVMScienceCORONARY-SINUS0206 medical engineeringCardiologyResearch and Analysis MethodsMembrane PotentialTECNOLOGIA ELECTRONICAMachine Learning Algorithms03 medical and health sciencesArtificial IntelligenceHeart Conduction SystemSupport Vector MachinesBody surfacemedicineComputer SimulationHeart AtriaCoronary sinusFibrillationbusiness.industryElectrophysiological TechniquesBiology and Life SciencesPattern recognitionAtrial arrhythmiasELECTROPHYSIOLOGY020601 biomedical engineeringMODELElectrophysiologyCardiovascular AnatomyCardiac ElectrophysiologyArtificial intelligencebusinessElectrocardiographyBiomarkersMathematics
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Identification of atrial fibrillation drivers by means of concentric ring electrodes

2022

The prevalence of atrial fibrillation (AF) has tripled in the last 50 years due to population aging. High-frequency (DFdriver) activated atrial regions lead the activation of the rest of the atria, disrupting the propagation wavefront. Fourier based spectral analysis of body surface potential maps have been proposed for DFdriver identification, although these approaches present serious drawbacks due to their limited spectral resolution for short AF epochs and the blurring effect of the volume conductor. Laplacian signals (BC-ECG) from bipolar concentric ring electrodes (CRE) have been shown to outperform the spatial resolution achieved with conventional unipolar recordings. Our aimed was to…

TecnologiaAtrial FibrillationBody Surface Potential MappingHumansHealth InformaticsHeart AtriaElectrodesSistema cardiovascularComputer Science ApplicationsComputers in Biology and Medicine
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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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Recurrence quantification analysis as a tool for complex fractionated atrial electrogram discrimination

2012

International audience; Atrial fibrillation is the most encountered pathology of the heart rate. The reasons of its occurrence and its particular characteristics remain unknown, resulting from complex phenomena interaction. From these interactions emerges Complex Fractionated Atrial Electrograms (CFAE) which are useful for the ablation procedure. This study presents a method based on nonlinear data analysis, the Recurrence Quantification Analysis (RQA) applied on intracardiac atrial electrograms to detect CFAE particularities. The results obtained on areas previously tagged by a cardilogist show a good sensitivity to CFAE. Combination of RQA features offers a larger discrimination potential…

medicine.medical_specialty[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]0206 medical engineeringTreatment outcome[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology030204 cardiovascular system & hematologySensitivity and SpecificityIntracardiac injection03 medical and health sciences0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemInternal medicineAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedRetrospective Studiesmedicine.diagnostic_testbusiness.industryBody Surface Potential MappingReproducibility of ResultsAtrial fibrillation[ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemmedicine.disease020601 biomedical engineeringTreatment OutcomeSurgery Computer-AssistedRecurrence quantification analysis[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Cardiologybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingElectrocardiographyAlgorithms2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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