Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation

Yingjing Feng; Caroline Roney; Meleze Hocini; Steven Niederer; Edward Vigmond

doi:10.22489/CinC.2020.473

Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation

Yingjing Feng^*, Caroline Roney, Meleze Hocini, Steven Niederer, Edward Vigmond

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

1 Citation (Scopus)

Abstract

Ectopic beats (EBs) generated from the atria or pulmonary veins are an important trigger mechanism for atrial fibrillation (AF). They can be periodic, and have been commonly observed during AF episodes. Robust noninvasive detection of EBs could improve pre-operative prediction, as well as post-ablation management. By separating periodic sources from surface ECG using second-order blind source separation methods, EBs were extracted, and discriminated from AF reentries, another type of periodic source. Our method is robust to noise of up to 0.5mV in the ECG, achieving an area-under curve of receiver operating characteristic (AUC-ROC) of 0.89±0.01 over a synthetic dataset of 31 reentries and 58 EBs, with and without Acetylcholine modulation in the left atrium.

Original language	English
Title of host publication	2020 Computing in Cardiology, CinC 2020
Publisher	IEEE Computer Society
ISBN (Electronic)	9781728173825
DOIs	https://doi.org/10.22489/CinC.2020.473
Publication status	Published - 13 Sept 2020
Event	2020 Computing in Cardiology, CinC 2020 - Rimini, Italy Duration: 13 Sept 2020 → 16 Sept 2020

Publication series

Name	Computing in Cardiology
Volume	2020-September
ISSN (Print)	2325-8861
ISSN (Electronic)	2325-887X

Conference

Conference	2020 Computing in Cardiology, CinC 2020
Country/Territory	Italy
City	Rimini
Period	13/09/2020 → 16/09/2020

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10.22489/CinC.2020.473

Cite this

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title = "Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation",

abstract = "Ectopic beats (EBs) generated from the atria or pulmonary veins are an important trigger mechanism for atrial fibrillation (AF). They can be periodic, and have been commonly observed during AF episodes. Robust noninvasive detection of EBs could improve pre-operative prediction, as well as post-ablation management. By separating periodic sources from surface ECG using second-order blind source separation methods, EBs were extracted, and discriminated from AF reentries, another type of periodic source. Our method is robust to noise of up to 0.5mV in the ECG, achieving an area-under curve of receiver operating characteristic (AUC-ROC) of 0.89±0.01 over a synthetic dataset of 31 reentries and 58 EBs, with and without Acetylcholine modulation in the left atrium.",

author = "Yingjing Feng and Caroline Roney and Meleze Hocini and Steven Niederer and Edward Vigmond",

note = "Funding Information: Funding has been received from the European Union Horizon 2020 research and Innovation programme “Personalised In-silico Cardiology (PIC)” under the Marie Sklodowska-Curie grant agreement No 764738, and the French National Research Agency (ANR-10-IAHU-04). Publisher Copyright: {\textcopyright} 2020 Creative Commons; the authors hold their copyright. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 2020 Computing in Cardiology, CinC 2020 ; Conference date: 13-09-2020 Through 16-09-2020",

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doi = "10.22489/CinC.2020.473",

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Feng, Y, Roney, C, Hocini, M, Niederer, S & Vigmond, E 2020, Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation. in 2020 Computing in Cardiology, CinC 2020., 9344190, Computing in Cardiology, vol. 2020-September, IEEE Computer Society, 2020 Computing in Cardiology, CinC 2020, Rimini, Italy, 13/09/2020. https://doi.org/10.22489/CinC.2020.473

Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation. / Feng, Yingjing; Roney, Caroline; Hocini, Meleze et al.
2020 Computing in Cardiology, CinC 2020. IEEE Computer Society, 2020. 9344190 (Computing in Cardiology; Vol. 2020-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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T1 - Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation

AU - Feng, Yingjing

AU - Roney, Caroline

AU - Hocini, Meleze

AU - Niederer, Steven

AU - Vigmond, Edward

N1 - Funding Information: Funding has been received from the European Union Horizon 2020 research and Innovation programme “Personalised In-silico Cardiology (PIC)” under the Marie Sklodowska-Curie grant agreement No 764738, and the French National Research Agency (ANR-10-IAHU-04). Publisher Copyright: © 2020 Creative Commons; the authors hold their copyright. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2020/9/13

Y1 - 2020/9/13

N2 - Ectopic beats (EBs) generated from the atria or pulmonary veins are an important trigger mechanism for atrial fibrillation (AF). They can be periodic, and have been commonly observed during AF episodes. Robust noninvasive detection of EBs could improve pre-operative prediction, as well as post-ablation management. By separating periodic sources from surface ECG using second-order blind source separation methods, EBs were extracted, and discriminated from AF reentries, another type of periodic source. Our method is robust to noise of up to 0.5mV in the ECG, achieving an area-under curve of receiver operating characteristic (AUC-ROC) of 0.89±0.01 over a synthetic dataset of 31 reentries and 58 EBs, with and without Acetylcholine modulation in the left atrium.

AB - Ectopic beats (EBs) generated from the atria or pulmonary veins are an important trigger mechanism for atrial fibrillation (AF). They can be periodic, and have been commonly observed during AF episodes. Robust noninvasive detection of EBs could improve pre-operative prediction, as well as post-ablation management. By separating periodic sources from surface ECG using second-order blind source separation methods, EBs were extracted, and discriminated from AF reentries, another type of periodic source. Our method is robust to noise of up to 0.5mV in the ECG, achieving an area-under curve of receiver operating characteristic (AUC-ROC) of 0.89±0.01 over a synthetic dataset of 31 reentries and 58 EBs, with and without Acetylcholine modulation in the left atrium.

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ER -

Robust Atrial Ectopic Beat Classification from Surface ECG Using Second-Order Blind Source Separation

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