Multi- and monofractal indices of short-term heart rate variability

R. Fisher, Metin Akay, P. Castiglioni, M. Di Rienzo

Research output: Contribution to journalArticlepeer-review


Indices of heart rate variability (HRV) based on fractal signal models have recently been shown to possess value as predictors of mortality in specific patient populations. To develop more powerful clinical indices of HRV based on a fractal signal model, the study investigated two HRV indices based on a monofractal signal model called fractional Brownian motion and an index based on a multifractal signal model called multifractional Brownian motion. The performance of the indices was compared with an HRV index in common clinical use. To compare the indices, 18 normal subjects were subjected to postural changes, and the indices were compared on their ability to respond to the resulting autonomic events in HRV recordings. The magnitude of the response to postural change (normalised by the measurement variability) was assessed by analysis of variance and multiple comparison testing. Four HRV indices were investigated for this study: the standard deviation of all normal R-R intervals, an HRV index commonly used in the clinic; detrended fluctuation analysis, an HRV index found to be the most powerful predictor of mortality in a study of patients with depressed left ventricular function; an HRV index developed using the maximum likelihood estimation (MLE) technique for a monofractal signal model; and an HRV index developed for the analysis of multifractional Brownian motion signals. The HRV index based on the MLE technique was found to respond most strongly to the induced postural changes (95% Cl). The magnitude of its response (normalised by the measurement variability) was at least 25% greater than any of the other indices tested.

Original languageEnglish
Pages (from-to)543-549
Number of pages7
JournalMedical and Biological Engineering and Computing
Issue number5
Publication statusPublished - Sep 2003


  • Detrended fluctuation analysis
  • Fractional Brownian motion
  • Heart rate variability
  • Maximum likelihood estimation
  • Multifractal

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management
  • Computer Science Applications
  • Computational Theory and Mathematics


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