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The paper introduces a new methodology of heart rate variability(HRV) in time-frequency analysis, which is based on Hilbert-Huang transform. We adopt the empirical mode decompostition(EMD) technique to decompose the R-R interval series into several mono-component signals which become analytic signal by means of Hilbert transform. So a novel algorithm based on Hilbert-Huang transform is proposed to extract the features of HRV signals. The numerical simulation results presented herein show the method can be used to identify the low-frequency and high-frequency bands of HRV more sharply and effectively through Hilbert spectrum than using the Fourier spectrum.