Fractal behaviour of heart rate variability reflects severity in stroke patients

Gianni d'addio, Graziamaria Corbi, Agostino Accardo, Giovanna Russo, Nicola Ferrara, M. Cristina Mazzoleni, Tanja Princi

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


Non-linear parameters obtained from heart rate variability (HRV) analysis has recently been recognized to provide valuable information for physiological interpretation of heart rate fluctuation. Among the numerous nonlinear parameters related to the fractal behaviour of the HRV signal, two classes have gained wide interest in the last years: the beta exponent based on the 1/f-like relationship, starting from the spectral power, and that based on fractal dimension. In order to evaluate the relationship between lesion's severity and fractal behaviour, 20 first-ever stroke subjects and 10 healthy subjects were studied. Patients were divided in two groups according to single or multiple medium cerebral artery lesions. All subjects underwent 24-hour Holter recording analysed by fractal and 1/f-like techniques. Differently from methods usually used in literature to evaluate the fractal dimension (FD), in this work the FD was extracted by using the Higuchi's algorithm that permits to calculate the parameter directly from the HRV sequences in the time domain. Results show that fractal analysis contains relevant information related to different HRV dynamics that permits to separate normal subjects from stroke patients. FD is also able to distinguish between normal and stroke subjects with different lesion's severity.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Number of pages5
Publication statusPublished - 2009
Event22nd International Conference on Medical Informatics Europe, MIE 2009 - Sarajevo, Bosnia and Herzegovina
Duration: Aug 30 2009Sep 2 2009


Other22nd International Conference on Medical Informatics Europe, MIE 2009
Country/TerritoryBosnia and Herzegovina


  • Beta exponent
  • Fractal dimension
  • Higuchi's algorithm
  • Hrv
  • Stroke

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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