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Updated: Jun 22, 2026
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Published on: June 27, 2013
Electroencephalographic analysis for the assessment of hepatic encephalopathy: comparison of non-parametric and
P Amodio1, R Orsato, P Marchetti
1Clinical Medicine 5, University of Padova, Padova, Italy.
Objective:
To compare electroencephalographic spectral analysis obtained by periodogram (calculated by means of Fast Fourier Transform) and autoregressive (AR) modelling for the assessment of hepatic encephalopathy.
Methods:
The mean dominant frequency (MDF) and the relative power of delta, theta, alpha, and beta bands were computed by both techniques from the electroencephalograms (EEG) of 201 cirrhotics and were evaluated in the clinical and prognostic assessment of the patients.
Results:
The values of all the five indexes computed by periodogram and AR modelling matched each other, but the latter provided stable values after the analysis of fewer epochs. Independently of the technique, the relative power of theta and alpha bands fitted the clinical data and had prognostic value. The relative power of beta and delta bands computed by AR modelling fitted more closely with clinical data fitted the clinical data more closely.
Conclusions:
The electroencephalographic spectral indexes obtained by periodogram and AR modelling were found to be, on average, undistinguishable, but the latter appeared less sensitive to noise and provided a more reliable assessment of low-power bands.
