Exploring the fractal complexity of cardiac variability in Epilepsy

This study explores the fractal dimension of heart rate variability (HRV) time series in individuals with epilepsy and healthy controls, using algorithms inspired by fractal geometry such as the chaos game and Sierpinski structures. The boxcounting method was employed to estimate the fractal dimension (FD) and compare its behavior across groups. Results indicate reduced fractal complexity in patients with epilepsy, which may reflect autonomic dysfunction associated with the condition. The integration of mathematical and medical analysis offers a new perspective on the study of complex physiological signals.