title: Assessment of cardiovascular autonomic control by the empirical mode decomposition.
abstract: OBJECTIVE
  Heart-rate variability (HRV) is an interesting tool for assessing cardiac autonomic system control, but nonstationarities raise problematic issues. The objective of this paper is to show that adapted signal processing tools may cope with nonstationary situations and improve the analysis of HRV.
  
  
  METHODS
  We propose to use the recent method of Empirical Mode Decomposition (EMD), so as to analyze the cardiac sympatho-vagal balance on automatically extracted modes. The method, which is fully data-adaptive, consists in an iterative decomposition based on the idea that any signal can be locally represented as an oscillation superimposed to a more regular trend. When a signal is composed of distinct nonstationary components, EMD therefore achieves a time-varying filtering which effectively separates them.
  
  
  RESULTS
  The method has been applied to situations where postural changes occur, provoking instantaneous changes in heart rate as a result of autonomic modifications. In the considered application where the sympatho-vagal balance is quantified by comparing the low-frequency (LF) and high-frequency (HF) components of RR intervals, EMD automatically achieves a separation of these components upon which further processing can be carried. Visualizing the decomposition in the time-frequency plane, we can identify local events due to the postural changes, and we can assess a (time-varying) HF vs. LF discrimination without resorting to some fixed high-pass/low-pass filtering.
  
  
  CONCLUSIONS
  Assessing cardiovascular autonomic control by resorting to LF/HF measurements may prove difficult in nonstationary situations where the use of a priori fixed filters can be questioned. Because it is both local and fully data-adaptive, EMD appears as an appealing and versatile pre-processing technique for overcoming some of the limitations that conventional spectral methods are faced with in nonstationary situations.
authors.affiliation: Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46, Allée d'Italie, 69364 Lyon Cedex 07, France.
authors.forename: E P
authors.initials: EP
authors.lastname: Souza Neto
authors.forename: M A
authors.initials: MA
authors.lastname: Custaud
authors.forename: J C
authors.initials: JC
authors.lastname: Cejka
authors.forename: P
authors.initials: P
authors.lastname: Abry
authors.forename: J
authors.initials: J
authors.lastname: Frutoso
authors.forename: C
authors.initials: C
authors.lastname: Gharib
authors.forename: P
authors.initials: P
authors.lastname: Flandrin
mesh_terms: D000328:Adult; D001341:Autonomic Nervous System / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D011187:Posture / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013057:Spectrum Analysis; D013997:Time Factors