论文信息 - Study on the optimal order for the auto-regressive time-frequency analysis of heart rate variability

Study on the optimal order for the auto-regressive time-frequency analysis of heart rate variability

Time-frequency analysis of heart rate variability (HRV) makes it easier to evaluate how the balance between the sympathetic and parasympathetic influences on heart rhythm varies with time. The auto-regressive model can be used to calculate the power spectrum density of HRV and to create an auto-regressive spectrogram. This work presents these techniques and describes a series of tests performed with the goal of determining the AR order that is more adequate for the calculation of the AR spectrogram. As a result, ranges of optimal orders for different interpolation rates of the HRV signal are presented.

[1] H. Akaike. Power spectrum estimation through autoregressive model fitting , 1969 .

[2] H. Akaike. A new look at the statistical model identification , 1974 .

[3] E. Parzen. Some recent advances in time series modeling , 1974 .

[4] Hirotugu Akaike,et al. On entropy maximization principle , 1977 .

[5] G. Schwarz. Estimating the Dimension of a Model , 1978 .

[6] H. Akaike. A Bayesian analysis of the minimum AIC procedure , 1978 .

[7] J. Rissanen. A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH , 1983 .

[8] W. M. Carey,et al. Digital spectral analysis: with applications , 1986 .

[9] Adson Ferreira da Rocha,et al. A tool for time-frequency analysis of heart rate variability , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).