Signal Fingerprinting as a Novel Diagnostic Tool to Identify Conduction Inhomogeneity

Ziliang Ye, Mathijs S. van Schie, Natasja M.S. de Groot*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


Background: Inhomogeneous intra-atrial conduction facilitates both initiation and perpetuation of atrial fibrillation (AF) and is reflected in electrogram (EGM) morphology. Objective: The primary objective of this study is to investigate regional differences in features of different EGM types during sinus rhythm (SR) and to design a patient-specific signal fingerprint, which quantifies the severity and extensiveness of inhomogeneity in conduction. Methods: Patients (N = 189, 86% male; mean age 65 ± 9 years) undergoing coronary artery bypass grafting (CABG) underwent high-resolution mapping of the right atrium (RA), left atrium (LA), and pulmonary vein area (PVA) including Bachmann’s bundle (BB). EGMs during 5 s of SR were classified as single potentials (SPs), short double potentials (SDPs, interval between deflections < 15 ms), long double potentials (LDPs, deflection interval > 15 ms), or fractionated potentials (FPs, ≥3 deflections). Of all SPs, differences in relative R- and S-wave amplitude were calculated (R/S ratios). Time difference between first and last deflection was determined (fractionation duration, FD) and potentials with amplitudes < 1.0 mV were labeled as low-voltage. Conduction block (CB) was defined as a difference in local activation time (LAT) between adjacent electrodes of ≥12 ms. Results: A total of 1,763,593 EGMs (9,331 ± 3,336 per patient) were classified (Table 1). Conclusion: The signal fingerprint, consisting of quantified EGM features, including the R/S ratio of SPs, the relative frequency distribution of unipolar voltages, the proportion of low-voltage areas, the proportion of the different types of EGMs, and durations of LDP and FDP, may serve as a diagnostic tool to determine the severity and extensiveness of conduction inhomogeneity. Further studies are required to determine whether the signal fingerprint can be used to identify patients at risk for AF onset or progression.

Original languageEnglish
Article number652128
JournalFrontiers in Physiology
Publication statusPublished - 26 Mar 2021


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