Analysis of Numerical ECG Parameters in Patients with Atrial Fibrillation: A Descriptive and Statistical Study Based on the ECG-ViEW II Database
Atrial fibrillation (AF) is the most common persistent cardiac arrhythmia in clinical practice and a significant, often underdiagnosed risk factor for stroke. The electrocardiogram (ECG) is the primary method for its detection, typically manifesting as irregular $\mathbf{R R}$ intervals and the absence of P-waves. Numerical ECG parameters enable quantitative analysis of these changes and provide a foundation for the development of automated detection systems. This study examines the association between atrial fibrillation and numerical ECG parameters using the ECG-ViEW II database. From 12-lead ECG recordings, key temporal and morphological parameters were extracted, and descriptive statistics were calculated to form the final dataset. Descriptive statistical analysis, inferential tests, and graphical visualizations were applied to compare AF and non-AF groups. The results indicate that parameters describing RR-interval variability show a strong association with atrial fibrillation, confirming their potential for application in automated systems for early AF detection.