Abstract:
Spectral parameters extracted from the heart rate variability signal are obtained
on a beat-to-beat basis by means of autoregressive recursive identification. In this
paper a whale forgetting window is introduced, instead of the classical exponential
one, in order to reduce the noise influence on the estimated parameters. After proper
simulation it was found that the whale forgetting window markedly reduces the noise
in the identification, but maintains a good response to abrupt changes in the signal.
The algorithm was thus applied to the analysis of the HRV data recorded during differenttransient
situations in physiological and pathological conditions. The spectral parameters were
obtained on a beat-to-beat basis and their trends were smoother and more accurate
with respect to the traditional exponential window also in presence of noise or artifacts
in the time series (sudden and short time changes, ectopic beats, etc.), without losing
the signal variations of physiological interest.
Keywords:
Recursive Identification - Autoregressive Model - Heart Rate Variability
