Key result
Comparing seven ECG algorithms establishes a framework to extract dominant frequency insights during cardiac arrhythmias.
Why the study?
Estimating cardiac arrhythmia frequency becomes increasingly challenging as ECG morphology becomes more complex, such as during transitions from tachycardia to fibrillation.
This study provides a comparative framework of seven time- and frequency-domain algorithms for analyzing cardiac arrhythmia frequency from complex ECG signals.
May guide algorithm selection in arrhythmia research; leaves open clinical validation and adoption.
During cardiac arrhythmia, the heart frequency is an important physiological parameter that can be identified by analyzing electrocardiogram (ECG) signals. However, the accuracy of the frequency estimation becomes increasingly challenging as the ECG morphology becomes more complex, for example, during transitions from tachycardia to fibrillation. In this paper, the authors compare seven conventional and novel time- and frequency-domain methods for cardiac arrhythmia frequency analysis, including an algorithm used in implantable cardioverter defibrillators. The objective of this study is to identify the approaches that reveal the potential presence of a dominant frequency and its role in characterizing different arrhythmia types. By evaluating the strengths and weaknesses of each method, the authors aim to establish an informative framework for extracting meaningful insights from electrocardiogram data in the context of cardiac arrhythmia frequency. In order to ascertain the statistical relevance of the methods, a dataset comprising 112 ECGs from arrhythmic murine hearts was analyzed. Additionally, a dataset comprising human arrhythmia data was examined to validate the techniques presented. The R-library, which contains the frequency determination algorithms, as well as the murine data set, is made available to the reader for the purposes of further testing and supplementation.
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Diaz-Maue et al. (2026) studied Cardiac arrhythmia (n=112). Seven time- and frequency-domain methods for cardiac arrhythmia frequency analysis vs. Each other was evaluated on Accuracy of frequency estimation and potential presence of a dominant frequency. Comparison of seven time- and frequency-domain algorithms on 112 murine and additional human ECGs established an informative framework for extracting dominant frequency insights during cardiac arrhythmias.
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