Ultradian rhythms during day and night in normal and COPD subjects

Agostino Accardo, Monica Cusenza, Alberto De Felice, Elisa Fornasa, Giovanni D'Addio

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


The analysis of heart rate variability (HRV) is a powerful tool in the study of the autonomic control of the heart. While circadian HRV rhythms have widely been characterized by traditional spectral measures, ultradian oscillations are not commonly investigated. In this study the identification of HRV ultradian rhythms is assigned to a quantitative measure characterizing the fractal-like behavior of the time series: the fractal dimension (FD). In order to assess ultradian regulation in Chronic Obstructive Pulmonary Disease (COPD) 24-h Holter ECG recordings of 52 COPD and 10 normal (healthy) subjects were analyzed. The FD was calculated by Higuchi's algorithm both during daytime and nighttime to highlight possible wake-sleep states differences. All subjects showed a similar common rhythm (0.06mHz) that persists with generally higher amplitude during night-time. A further rhythm becomes predominant in normal subjects in the dayto-night transition (0.15mHz), probably under the influence of the REM/non-REM ultradian sleep cycle. A very large difference between night and day amplitudes of this rhythm and of the next one (at about 0.22mHz) characterize the HRV fractal dimension of the Normal in respect of COPD. In conclusion, the FD could be used as a marker of ultradian cardiac autonomic regulation providing new insights into autonomic physiology of normal and COPD patients.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Number of pages3
Publication statusPublished - 2012
Event24th Medical Informatics in Europe Conference, MIE 2012 - Pisa, Italy
Duration: Aug 26 2012Aug 29 2012


Other24th Medical Informatics in Europe Conference, MIE 2012


  • COPD
  • Fractal dimension
  • HRV
  • Ultradian rhythms

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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