Nonlinear analysis of HRV has recently been recognized to provide valuable information in the
prognostic classification of cardiac patients. Among the numerous non-linear parameters related to the fractal
behaviour of the HRV signal, two classes have gained wide interest in the last years: that based on the 1/flike
relationship, starting from the spectral power, and that based on fractal features. We present results
obtained from the analysis of 50 heart rate variability series which have been extracted from Holter
recordings in the 24-hours in normal subjects and pathological patients. Data have been collected inside a
multicentric research program, which aimed at the nonlinear analysis of heart rate variability series.
Differently from methods usually used in literature to evaluate the fractal dimension, the parameter used in
this work has been extracted directly from the HRV sequences in the time domain, by means of the Higuchi's
algorithm. Results show that this fractal dimension can be used to separate normal subjects from patients
suffering from cardiovascular diseases and to evaluate the presence of circadianity in the HRV over the
whole twenty four hours.
