Analysis of heart rate variability using power spectral analysis and nonlinear dynamics

It is well known that the heart rate variability (HRV) reflects the activity of the autonomic nervous system. Irregular variance of HRV can be considered as a predictor for sudden cardiac death (SCA) or the index of reinnervation in the cardiac transplant patient, etc. Measurements of HRV can be acquired by analysing the changes of heart rate with power spectral analysis or obtained from the visual patterns (attractor) by using the nonlinear dynamics (chaos theory). There are no significant different between fast Fourier transformation and autoregressive estimation for the evaluation of HRV spectra, and there were certain patterns displayed with nonlinear dynamics.<>