A Novel spectral Analysis Method of Atrial Fibrillation Signal Based on Hilbert-Huang Transform

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. Fourier spectrum analysis provides a common framework for examining the distribution of global energy in the frequency domain. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. Atrial fibrillation (AF) is a complex nonlinear pathological phenomena, and recently receives a significant amount of research effort. In this work we develop a new signal processing method using Hilbert-huang transform to perform spectral analysis of the atrial fibrillation signals (AFs). This method provides a new analysis tool for AFs. Our experimental results show that it improves the spectral resolution and enables us to understand the episode of AF more precisely