AUTHOR=Diaz-Maue Laura , Witt Annette , Elshareif  Lina , Nobach Holger 
  
TITLE=Unraveling cardiac arrhythmia frequency: comparative analysis using time and frequency domain algorithms
  
JOURNAL=Frontiers in Signal Processing
  
VOLUME=Volume 5 - 2025
  
YEAR=2026
  
URL=https://www.frontiersin.org/journals/signal-processing/articles/10.3389/frsip.2025.1707422
  
DOI=10.3389/frsip.2025.1707422
  
ISSN=2673-8198
  
ABSTRACT=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.