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Chinese Journal of Electrical Engineering 2023, 9(1): 93-103 https://doi.org/10.23919/CJEE.2023.000008
Special Issue Paper | Open Access | Issue | Published: 31 March 2023

Review of Ex Vivo Cardiac Electrical Mapping and Intelligent Labeling of Atrial Fibrillation Substrates

Show Author's Information Yi Chang1,  Ming Dong1( ),  Bin Wang1,  Ming Ren1,  Lihong Fan2
School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
Keywords:
deep learning, Catheter ablation, atrial fibrillation substrate, three-dimensional mapping
Cite this article:
Chang Y, Dong M, Wang B, et al. Review of Ex Vivo Cardiac Electrical Mapping and Intelligent Labeling of Atrial Fibrillation Substrates. Chinese Journal of Electrical Engineering, 2023, 9(1): 93-103. https://doi.org/10.23919/CJEE.2023.000008
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Abstract Full text About this article

With the development of computer hardware and the growth of clinical database, tremendous progress has been made in the application of deep learning to electrocardiographic data, which provides new ideas for the ex vivo cardiac electrical mapping of atrial fibrillation (AF) substrates. The AF mechanism and current status of AF substrate research are first summarized. Then, the advantages and limitations of cardiac electrophysiological mapping techniques are analyzed. Finally, the application of deep learning to electrocardiogram (ECG) data is reviewed, the problems with the ex vivo intelligent labeling of an AF substrate and the possible solutions are discussed, an outlook on future development is provided.


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About this article

Review of Ex Vivo Cardiac Electrical Mapping and Intelligent Labeling of Atrial Fibrillation Substrates

Show Author's information Yi Chang1, Ming Dong1( ), Bin Wang1, Ming Ren1, Lihong Fan2
School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China

Abstract

With the development of computer hardware and the growth of clinical database, tremendous progress has been made in the application of deep learning to electrocardiographic data, which provides new ideas for the ex vivo cardiac electrical mapping of atrial fibrillation (AF) substrates. The AF mechanism and current status of AF substrate research are first summarized. Then, the advantages and limitations of cardiac electrophysiological mapping techniques are analyzed. Finally, the application of deep learning to electrocardiogram (ECG) data is reviewed, the problems with the ex vivo intelligent labeling of an AF substrate and the possible solutions are discussed, an outlook on future development is provided.

Keywords: deep learning, Catheter ablation, atrial fibrillation substrate, three-dimensional mapping

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Received: 30 September 2022
Revised: 31 December 2022
Accepted: 30 January 2023
Published: 31 March 2023
Issue date: March 2023

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