Atrial Fibrillation (AF), commonly referred to as AFib in clinical medicine, is the most prevalent type of cardiac arrhythmia. Atrial Fibrillation manifests when the electrical excitation wave propagates through the atria without a defined spatial direction or coordinated pathway. This paper analyzes the electrocardiogram (ECG) signals of adults, benchmarking healthy individuals against those diagnosed with Atrial Fibrillation. The dataset utilized in this study was compiled by the American and European Heart Associations. Regarding the demographic distribution, less than 5% of the subjects fall within the 40–50 age bracket, while 5–15% are in the octogenarian category (around 80 years old). Based on the quantitative investigations, the heart rate in patients suffering from Atrial Fibrillation exhibits highly irregular dynamics and elevated magnitudes, consistently clustering in the range of 80 to 100 beats per minute (bpm), and frequently exceeding 100 bpm. Furthermore, statistical feature extraction reveals that individuals with Atrial Fibrillation present a significantly lower mathematical mean, alongside markedly higher entropy and energy values in their processed ECG signal segments compared to healthy cohorts.