Abstract

Background and Objectives:The extensive collection of electrocardiogram (ECG) recordings stored in paper format has provided opportunities for numerous digitization studies. However, the traditional 10 s 12-lead ECG printout typically splits the ECG signals into four asynchronous sections of 3 leads and 2.5 s each. Since each lead corresponds to different time instants, developing a synchronization method becomes necessary for applications such as vectorcardiogram (VCG) reconstruction. Methods:A beat-level synchronization method has been developed and validated using a dataset of 21,674 signals. This method effectively addresses synchronization distortions caused by RR interval variations and preserves the time lags between R peaks across different leads for each beat. Results:The results demonstrate that the proposed method successfully synchronizes the ECG, allowing a VCG reconstruction with an average Pearson Correlation Coefficient of 0.9815±0.0426. The Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Error (MAE) values for the reconstructed VCG are 0.0248±0.0214 mV and 0.0133±0.0123 mV, respectively. These metrics indicate the reliability of the VCG reconstruction achieved by means of the proposed synchronization method. Conclusions:The synchronization method has demonstrated its robustness and high performance compared to existing techniques in the field. Its effectiveness has been observed across a wide variety of signals, showcasing its applicability in real clinical environments. Moreover, its ability to handle a large number of signals makes it suitable for various applications, including retrospective studies and the development of machine learning methods.

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