Fractal Behaviour Of Pathological Heart Rate
Variability Dynamics
Author(s)
G. D’Addio, A. Accardo, G. Corbi, F. Rengo & N. Ferrara
Abstract
Heart rate variability analysis (HRV) is a well recognized tool in the autonomic
control assessment. It has been suggested that nonlinear analysis of HRV might
provide more valuable information than traditional linear methods. Several non
linear fractal techniques recently gained wide interest: that based on indirect
fractal dimension (FD) estimation from the 1/f spectral power relationship, and
that based on a direct FD estimation from HRV time sequences. Aim of the study
was to assess whether FD discriminates pathological HRV dynamics, comparing
results with normal subjects and traditional linear indexes. We studied 7 groups
of 10 ECG 24h-Holter recordings in normal and different pathologies:
obstructive pulmonary disease, stroke, hypertension, post myocardial infarction,
heart failure, heart transplanted. HRV was assessed by spectral power in very
low, low and high frequency bands and standard deviation between normal beats.
FD was estimated directly from the HRV sequences by Higuchi method (HM)
and from the 1/f slope of spectral power relationship (beta). Results showed
differences in the autonomic control impairments better described by FD than by
traditional linear methods. Although HM and beta tried to measure the same FD
property, the latter seemed to be rather insensitive to changes in autonomic
control. These preliminary results clearly suggest that FD, estimated by HM,
contains relevant information related to different HRV pathological dynamics.
Keywords: HRV, fractal analysis, nonlinear dynamics.
Keywords
HRV, fractal analysis, nonlinear dynamics.
Related Book
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