About: Early Signs of Critical Slowing Down in Heart Surface Electrograms of Ventricular Fibrillation Victims

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Early Signs of Critical Slowing Down in Heart Surface Electrograms of Ventricular Fibrillation Victims Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Early Signs of Critical Slowing Down in Heart Surface Electrograms of Ventricular Fibrillation Victims
Creator	Ashikaga, Hiroshi Bernus, Olivier Dubois, Remi Haïssaguerre, Michel Hocini, Mélèze Nannes, Berend Quax, Rick
Source	PMC
abstract	Ventricular fibrillation (VF) is a dangerous type of cardiac arrhythmia which, without intervention, almost always results in sudden death. Implantable automatic defibrillators are among the most successful devices to prevent sudden death by automatically applying a shock to the heart when fibrillation occurs. However, the electric shock is very painful and could lead to dangerous situations when a patient is, for example, driving or biking. An early warning signal for VF could reduce the risk in such situations or, in the future, reduce the need for defibrillation altogether. Here, we test for the presence of critical slowing down (CSD), which has proven to be an early warning indicator for critical transitions in a range of different systems. CSD is characterized by a buildup of autocorrelation; we therefore study the residuals of heart surface electrocardiograms (ECGs) of patients that suffered VF to investigate if we can measure positive trends in autocorrelation. We consider several methods to extract these residuals from the original signals. For three out of four VF victims, we find a significant amount of positive autocorrelation trends in the residuals, which might be explained by CSD. We show that these positive trends may not be measurable from the original body surface ECGs, but only from certain areas around the heart surface. We argue that additional experimental studies involving heart surface ECG data of subjects that did not suffer VF are required to quantify the prediction accuracy of the promising results we get from the data of VF victims.
has issue date	2020-05-23(xsd:dateTime)
bibo:doi	10.1007/978-3-030-50423-6_25
has license	no-cc
sha1sum (hex)	b4e88ac8d3aaf295b438491bf03e1afb7fed862f
schema:url	https://doi.org/10.1007/978-3-030-50423-6_25
resource representing a document's title	Early Signs of Critical Slowing Down in Heart Surface Electrograms of Ventricular Fibrillation Victims
has PubMed Central identifier	PMC7303708
schema:publication	Computational Science - ICCS 2020
resource representing a document's body	covid:b4e88ac8d3aaf295b438491bf03e1afb7fed862f#body_text
is schema:about of	named entity 'slowing' named entity 'victims' named entity 'autocorrelation' named entity 'patient' named entity 'ECGs' named entity 'Heart' named entity 'studies' named entity 'indicator' named entity 'additional' named entity 'CSD' named entity 'driving' named entity 'suffer' named entity 'original' named entity 'positive' named entity 'dangerous' named entity 'critical' named entity 'data' named entity 'surface' named entity 'involving' named entity 'Heart' named entity 'cardiac arrhythmia' named entity 'experimental studies' named entity 'Ventricular fibrillation' named entity 'electric shock' named entity 'autocorrelation' named entity 'dangerous type' named entity 'sudden death' named entity 'autocorrelation' named entity 'chaotic attractor' named entity 'electrocardiogram' named entity 'Holter' named entity 'time series' named entity 'early repolarization' named entity 'ventricles' named entity 'QRS' named entity 'ECG' named entity 'ECG' named entity 'ECG' named entity 'ECG' named entity 'short-term' named entity 'ICD' named entity 'ECG leads' named entity 'probability' named entity 'Holter' named entity 'HRV' named entity 'null hypothesis' named entity 'heart chambers' named entity 'QRS' named entity 'significance testing' named entity 'autocorrelation' named entity 'autocorrelation' named entity 'autocorrelation' named entity 'autocorrelation' named entity 'root mean square' named entity 'heart rhythm' named entity 'ECGs' named entity 'medical conditions' named entity 'significance level' named entity 'QRS' named entity 'QRS' named entity 'complex systems' named entity 'autocorrelation' named entity 'ECG' named entity 'electrode' named entity 'electric shock' named entity 'ECG' named entity 'arrhythmia' named entity 'complex systems' named entity 'fitting method' named entity 'brain activity' named entity 'depolarization' named entity 'time series' named entity 'ICD' named entity 'ECG' named entity 'ECG' named entity 'heart rhythm' named entity 'fitting method'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software