Obianom Ekenedirichukwu N, Ng G André, Li Xin
Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.
Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom.
Front Physiol. 2025 Apr 25;16:1532284. doi: 10.3389/fphys.2025.1532284. eCollection 2025.
This paper aims to review the literature on 12-lead ECG reconstruction, highlight various algorithmic approaches and evaluate their predictive strengths. In addition, it investigates the implications of performing reconstruction in particular ways.
This narrative review analysed 39 works on the reconstruction of 12-lead ECGs, focusing on the algorithms used for reconstruction and the results gotten from using these algorithms.
The works analysed featured the use of as little as one lead and as much as four leads for reconstruction of the other leads. Linear and nonlinear (including artificial intelligence) algorithms showed promising performances. Their outputs had correlations of greater than 0.90 depending on how the reconstruction models were built.
Three leads are optimal as input predictors for minimal reconstruction errors, but there is no universal algorithm that applies to every reconstruction task. Both linear and nonlinear algorithms can achieve high correlations, and minimal root means square errors. Hence, planned steps are needed when deciding how to manipulate the data and build the models to achieve high accuracies.
本文旨在回顾关于12导联心电图重建的文献，突出各种算法方法并评估其预测优势。此外，还研究了以特定方式进行重建的影响。
本叙述性综述分析了39篇关于12导联心电图重建的论文，重点关注用于重建的算法以及使用这些算法所获得的结果。
所分析的论文中，用于重建其他导联的导联数量少至一根，多至四根。线性和非线性（包括人工智能）算法表现出良好的性能。根据重建模型的构建方式，其输出的相关性大于0.90。
三根导联作为输入预测因子可实现最小的重建误差，但不存在适用于每个重建任务的通用算法。线性和非线性算法均可实现高相关性和最小均方根误差。因此，在决定如何处理数据和构建模型以实现高精度时，需要有计划的步骤。
