Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37299
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dc.contributor.authorSTOKS, Job-
dc.contributor.authorVAN REES, Bianca-
dc.contributor.authorNguyen, Uyen-
dc.contributor.authorPeeters, Ralf-
dc.contributor.authorVolders, Paul-
dc.contributor.authorCluitmans, Matthijs-
dc.date.accessioned2022-05-13T11:16:56Z-
dc.date.available2022-05-13T11:16:56Z-
dc.date.issued2021-
dc.date.submitted2022-04-22T11:13:11Z-
dc.identifier.citation-
dc.identifier.issn2325-8861-
dc.identifier.urihttp://hdl.handle.net/1942/37299-
dc.description.abstractDynamic variability of ventricular activation and recovery can be a physiological phenomenon, but is also known to increase susceptibility to arrhythmias. It has been extensively studied on the 12-lead electrocardiogram (ECG), but subtle (patho)physiological variations may be challenging to detect and localize due to the limited spatial resolution. Electrocardiographic imaging (ECGI) could be a useful noninvasive high-resolution mapping technique to investigate ventricular dynamics in more detail. Ventricular activation and recovery times (ATs and RTs) were examined using ECGI in 10 normal subjects. Zero-th order Tikhonov regularization was used in combination with a spatiotemporal estimation method to determine ATs and RTs. Dynamics were defined as standard deviations of ventricular ATs and RTs over three beats. Dynamics were higher for recovery than for activation during sinus rhythm, and significantly exaggerated after ventricular ectopy. Left ventricular areas were less dynamic than right ventricular areas. Since arrhythmias may arise due to an increase in ventricular dynamics in the diseased heart, these results provide an important basis for future research on ventricular dynamics and arrhythmias.-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesComputing in Cardiology Conference-
dc.titleDynamics of Ventricular Electrophysiology Are Unmasked Through Noninvasive Electrocardiographic Imaging-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate2021, Sep 12-15-
local.bibliographicCitation.conferencenameConference on Computing in Cardiology (CinC)-
local.bibliographicCitation.conferenceplaceBrno, CZECH REPUBLIC-
dc.identifier.volume2021-
local.format.pages4-
local.bibliographicCitation.jcatC1-
local.publisher.place345 E 47TH ST, NEW YORK, NY 10017 USA-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.23919/CinC53138.2021.9662863-
dc.identifier.isi000821955000162-
dc.identifier.eissn2325-887X-
local.provider.typePdf-
local.bibliographicCitation.btitle2021 Computing in Cardiology (CINC)-
local.uhasselt.internationalyes-
item.contributorSTOKS, Job-
item.contributorVAN REES, Bianca-
item.contributorNguyen, Uyen-
item.contributorPeeters, Ralf-
item.contributorVolders, Paul-
item.contributorCluitmans, Matthijs-
item.fullcitationSTOKS, Job; VAN REES, Bianca; Nguyen, Uyen; Peeters, Ralf; Volders, Paul & Cluitmans, Matthijs (2021) Dynamics of Ventricular Electrophysiology Are Unmasked Through Noninvasive Electrocardiographic Imaging.-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
item.validationecoom 2023-
Appears in Collections:Research publications
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