Using Hilbert-Huang Transform (HHT) to Access sympathovagal balance
Using Hilbert-Huang Transform (HHT) to Access sympathovagal balance, Proc ISEC Conf. in Mathematical Methods in Engineering - MME 2010, Coimbra, Portugal, Vol. , pp. 157 - 177, October, 2010.
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Spectral analysis of heart rate and blood pressure signals is one of the
main procedures to study cardiovascular neuronal regulation. Classical spectral
techniques based on FFT (Fast Fourier Transform) are designed for stationary data
in linear systems. The non-stationarity and nonlinearity of this kind of data is a major
problem for classical spectral techniques. Wavelet analysis is able to tackle nonstationarity,
but nonlinearity remains an issue, and the choice of wavelet mother
poses a new constraint.
Hilbert-Huang Transform is a time-frequency signal processing technique that is
able to tackle both non-stationarity and nonlinearity, in which the basis functions are
data-driven. In this paper a method to access neuronal sympathovagal balance using
heart rate and blood pressure signals is presented, based on the Hilbert-Huang
Transform. In order to illustrate the method two examples are shown, with data from
the head-up tilt test and the deep breathing metronomic manoeuvre.