Deriving the respiratory sinus arrhythmia from the heartbeat time series using Empirical Mo.pdf
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Deriving the respiratory sinus arrhythmia
from the heartbeat time series using
Empirical Mode Decomposition
R. Balocchi a,?, D. Menicucci a, E. Santarcangelo b,
L. Sebastiani b, A. Gemignani b, B. Ghelarducci b, M. Varanini a
aIstituto di Fisiologia Clinica, CNR, via Moruzzi 1, 56124 Pisa, Italy
bDipartimento di Fisiologia e Biochimica, Universita? di Pisa, via San Zeno 31,
56127 Pisa, Italy
Abstract
Heart rate variability (HRV) is a well-known phenomenon whose characteristics
are of great clinical relevance in pathophysiologic investigations. In particular, res-
piration is a powerful modulator of HRV contributing to the oscillations at highest
frequency. Like almost all natural phenomena, HRV is the result of many nonlin-
early interacting processes; therefore any linear analysis has the potential risk of
underestimating, or even missing, a great amount of information content. Recently
the technique of Empirical Mode Decomposition (EMD) has been proposed as a new
tool for the analysis of nonlinear and nonstationary data. We applied EMD analysis
to decompose the heartbeat intervals series, derived from one electrocardiographic
(ECG) signal of 13 subjects, into their components in order to identify the modes
associated with breathing. After each decomposition the mode showing the highest
frequency and the corresponding respiratory signal were Hilbert transformed and
the instantaneous phases extracted were then compared. The results obtained in-
dicate a synchronization of order 1:1 between the two series proving the existence
of phase and frequency coupling between the component associated with breathing
and the respiratory signal itself in all subjects.
Key words: heart rate variability, empirical mode decomposition, respiratory sinus
arithmia, synchronization.
? Corresponding author.
Email address: balocchi@r.it (R. Balocchi).
Preprint submitted to Elsevier Science 5 February 2008
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