Fractal behaviour of pathological heart rate variability dynamics

G. D'Addio, A. Accardo, G. Corbi, F. Rengo, N. Ferrara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationWIT Transactions on Biomedicine and Health
Pages39-47
Number of pages9
Volume13
DOIs
Publication statusPublished - 2009
Event8th International Conference on Modelling in Medicine and Biology, BIOMED 2009 - Crete, Greece
Duration: May 26 2009May 28 2009

Other

Other8th International Conference on Modelling in Medicine and Biology, BIOMED 2009
CountryGreece
CityCrete
Period5/26/095/28/09

Fingerprint

Heart Rate Variability
Fractals
Fractal Dimension
Fractal
Fractal dimension
Heart Rate
Dynamic Analysis
Sequence Analysis
Dynamic analysis
Heart Failure
Myocardial Infarction
Hypertension
Obstructive Lung Diseases
Beat
Stroke
Nonlinear Analysis
Frequency standards
Pulmonary diseases
Standard deviation
Low Frequency

Keywords

  • Fractal analysis
  • HRV
  • Nonlinear dynamics

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Biomedical Engineering
  • Computer Science Applications
  • Modelling and Simulation

Cite this

D'Addio, G., Accardo, A., Corbi, G., Rengo, F., & Ferrara, N. (2009). Fractal behaviour of pathological heart rate variability dynamics. In WIT Transactions on Biomedicine and Health (Vol. 13, pp. 39-47) https://doi.org/10.2495/BIO090041

Fractal behaviour of pathological heart rate variability dynamics. / D'Addio, G.; Accardo, A.; Corbi, G.; Rengo, F.; Ferrara, N.

WIT Transactions on Biomedicine and Health. Vol. 13 2009. p. 39-47.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

D'Addio, G, Accardo, A, Corbi, G, Rengo, F & Ferrara, N 2009, Fractal behaviour of pathological heart rate variability dynamics. in WIT Transactions on Biomedicine and Health. vol. 13, pp. 39-47, 8th International Conference on Modelling in Medicine and Biology, BIOMED 2009, Crete, Greece, 5/26/09. https://doi.org/10.2495/BIO090041
D'Addio G, Accardo A, Corbi G, Rengo F, Ferrara N. Fractal behaviour of pathological heart rate variability dynamics. In WIT Transactions on Biomedicine and Health. Vol. 13. 2009. p. 39-47 https://doi.org/10.2495/BIO090041
D'Addio, G. ; Accardo, A. ; Corbi, G. ; Rengo, F. ; Ferrara, N. / Fractal behaviour of pathological heart rate variability dynamics. WIT Transactions on Biomedicine and Health. Vol. 13 2009. pp. 39-47
@inproceedings{1d19d17ece9c4cb9bec27bb1818319ce,
title = "Fractal behaviour of pathological heart rate variability dynamics",
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 = "Fractal analysis, HRV, Nonlinear dynamics",
author = "G. D'Addio and A. Accardo and G. Corbi and F. Rengo and N. Ferrara",
year = "2009",
doi = "10.2495/BIO090041",
language = "English",
isbn = "9781845641832",
volume = "13",
pages = "39--47",
booktitle = "WIT Transactions on Biomedicine and Health",

}

TY - GEN

T1 - Fractal behaviour of pathological heart rate variability dynamics

AU - D'Addio, G.

AU - Accardo, A.

AU - Corbi, G.

AU - Rengo, F.

AU - Ferrara, N.

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Fractal analysis

KW - HRV

KW - Nonlinear dynamics

UR - http://www.scopus.com/inward/record.url?scp=71649089060&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71649089060&partnerID=8YFLogxK

U2 - 10.2495/BIO090041

DO - 10.2495/BIO090041

M3 - Conference contribution

SN - 9781845641832

VL - 13

SP - 39

EP - 47

BT - WIT Transactions on Biomedicine and Health

ER -