The heart rate variability (HRV) signal carries important information about the systems
controlling heat rate and blood pressure, mainly elicited by autonomic nervous system
(sympathetic and parasympathetic) controls. The present paper illustrates methods of HRV
signal processing by using autoregressive (AR) modeling and power spectral density
estimate. The information enhanced in this way seems to be particularly sensitive in
discriminating various cardiovascular pathologies (hypertension, myocardial infarction …