Abstract
A parametric method of spectral analysis, the AutoRegressive (AR) modellization, was applied in the study of Heart Rate Variability (HRV) signal obtained from sleeping subjects. Different periods of sleep were selected from a night recording and the HRV signal was obtained from the ECG in the form of interval tachogram (the series of RR intervals expressed in seconds as a function of the cardiac beat number). The AR model allowed an automatic spectral decomposition and the extraction of spectral parameters which can quantify the sympatho-vagal balance during the periods of sleep. In particular we studied the Low Frequency (LF, around 0.1 Hz) and the High Frequency (HF, synchronous with respiration) components, related to sympathetic and vagal activity, and their ratio LF/HF. Differences in the sympatho-vagal balance were found between REM and deep sleep. In particular the behavior of the
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