ECGVEDNET: A Variational Encoder-Decoder Network for ECG Delineation in Morphology Variant ECGs

Electrocardiogram (ECG) delineation to identify the fiducial points of ECG segments, plays an important role in cardiovascular diagnosis and care. Whilst deep delineation frameworks have been deployed within the literature, several factors still hinder their development: (a) data availability: the c...

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Veröffentlicht in:	IEEE transactions on biomedical engineering Jg. 71; H. 7; S. 2143 - 2153
Hauptverfasser:	Chen, Long, Jiang, Zheheng, Barker, Joseph, Zhou, Huiyu, Schlindwein, Fernando, Nicolson, Will, Ng, G. Andre, Li, Xin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Annotations Availability Biomedical engineering Computational modeling Databases, Factual Datasets Deep Learning Delineation ECG delineation EKG Electrocardiography Electrocardiography - methods Encoders-Decoders fiducial points detection Humans Knowledge management Morphology Performance degradation Signal processing algorithms Signal Processing, Computer-Assisted Source code Transfer learning Variation variational encoder-decoder
ISSN:	0018-9294, 1558-2531, 1558-2531
Online-Zugang:	Volltext
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