Extracting Atrial Activations from Intracardiac Signals during Atrial Fibrillation using Adaptive Mathematical Morphology.
Détails
Télécharger: BIB_1C8E38E921A4.P001.pdf (1430.25 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_1C8E38E921A4
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Extracting Atrial Activations from Intracardiac Signals during Atrial Fibrillation using Adaptive Mathematical Morphology.
Périodique
Computing in Cardiology
ISSN
2325-8861
ISSN-L
2325-8861
Statut éditorial
Publié
Date de publication
09/2015
Peer-reviewed
Oui
Editeur⸱rice scientifique
Murray A.
Volume
42
Pages
913-916
Langue
anglais
Notes
2015 Comp in Cardiol Conference (CinC)
Nice, FRANCE
Nice, FRANCE
Résumé
The detection of intracardiac activities is a major issue
in the processing of atrial fibrillation signals. we evaluate
a method based on mathematical morphology with
an adaptive structuring element in order to extract the
atrial activations from intracardiac electrograms. The
structuring element is continuously updated for each activation
based on the morphological characteristics of the
previously detected activations. A dataset of recordings
from patients with chronic atrial fibrillation who underwent
catheter ablation were used in order to evaluate the
performance of the proposed method. Results show high
performance compared to a dataset manually annotated
by an expert. The detection rate, sensitivity and positive
prediction value (PPV) were respectively 99.1% ,99.5%,
99.5%. The proposed method is fast and offers low computational
cost, which makes it a suitable approach for realtime/online
scenari
in the processing of atrial fibrillation signals. we evaluate
a method based on mathematical morphology with
an adaptive structuring element in order to extract the
atrial activations from intracardiac electrograms. The
structuring element is continuously updated for each activation
based on the morphological characteristics of the
previously detected activations. A dataset of recordings
from patients with chronic atrial fibrillation who underwent
catheter ablation were used in order to evaluate the
performance of the proposed method. Results show high
performance compared to a dataset manually annotated
by an expert. The detection rate, sensitivity and positive
prediction value (PPV) were respectively 99.1% ,99.5%,
99.5%. The proposed method is fast and offers low computational
cost, which makes it a suitable approach for realtime/online
scenari
Mots-clé
Cardiology - Atrial fibrillation - Electrophysiology - intracardiac signals - mathematical morphology
Web of science
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Création de la notice
10/03/2016 15:43
Dernière modification de la notice
29/07/2023 5:57