Synthetic ECG signals generation: A scoping review.

IF 7 2区 医学 Q1 BIOLOGY
Computers in biology and medicine Pub Date : 2025-01-01 Epub Date: 2024-11-28 DOI:10.1016/j.compbiomed.2024.109453
Beatrice Zanchi, Giuliana Monachino, Luigi Fiorillo, Giulio Conte, Angelo Auricchio, Athina Tzovara, Francesca D Faraci
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引用次数: 0

Abstract

The scientific community has recently shown increasing interest in generating synthetic ECG data. In particular, synthetic ECG signals can be beneficial for understanding cardiac electrical activity, developing large and heterogeneous unbiased datasets, and anonymizing data to favour knowledge sharing and open science. In the present scoping review, various methodologies to generate synthetic ECG data have been thoroughly analysed, highlighting their limitations and possibilities. A total of 79 studies have been included and classified, depending on the methodology employed, the number of leads, the number of heartbeats, and the purpose of data synthesis. Three main categories have been identified: mathematical modelling, computer vision inherited methods, and deep generative models. This thorough analysis can assist in the choice of the most suitable technique for a specific application. The biggest challenge is identifying standardized metrics that can comprehensively and quantitatively assess the fidelity and variability of generated synthetic ECG data.

合成心电信号的产生:范围综述。
科学界最近对合成心电数据越来越感兴趣。特别是,合成心电信号有助于理解心电活动,开发大型异构无偏数据集,并对数据进行匿名化,以促进知识共享和开放科学。在目前的范围审查,各种方法来产生合成心电数据已被彻底分析,突出其局限性和可能性。根据所采用的方法、线索数量、心跳次数和数据合成的目的,总共纳入了79项研究并进行了分类。已经确定了三个主要类别:数学建模,计算机视觉继承方法和深度生成模型。这种彻底的分析有助于为特定应用程序选择最合适的技术。最大的挑战是确定能够全面定量评估生成的合成心电数据的保真度和可变性的标准化指标。
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来源期刊
Computers in biology and medicine
Computers in biology and medicine 工程技术-工程:生物医学
CiteScore
11.70
自引率
10.40%
发文量
1086
审稿时长
74 days
期刊介绍: Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.
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