Empirical mode decomposition for frequency analysis of heart rate variability

The malignant ventricular tachyarrhythmia have the great harmfulness to life, so it is very important for prediction of ventricular arrhythmias. Sudden cardiac death can occur due to ventricular arrhythmia. The purpose of this work is to help physicians in early diagnosis of ventricular arrhythmia. Applying the right solution at the right time can help avoid the tragedy of sudden arrhythmic death. Heart rate variability (HRV) represents one of the most promising quantitative markers of autonomic activity. There are various time and frequency domain parameters related to HRV which helps in diagnosis of various disorders. This paper aims to take into consideration the parametric method which gives a smoother spectral component, which can be distinguished independently of preselected frequency bands. The proposed method of heart rate variability analysis in frequency domain includes decomposition of RR interval using Empirical mode decomposition (EMD) which is followed by Hilbert spectral analysis of the decomposed functions. This method of analysis is so called Hilbert-Huang transform (HHT) method which is a novel method for analyzing non-linear and non-stationary signals and it is applicable to nonlinear and non-stationary processes. High frequency (HF) component of the total power reflects parasympathetic activity low frequency (LF) component is the result of sympathetic and parasympathetic activity.