Entropy of the EEG in transition to burst suppression in deep anesthesia: Surrogate analysis.

In this paper 5 methods for the assessment of signal entropy are compared in their capability to follow the changes in the EEG signal during transition from continuous EEG to burst suppression in deep anesthesia. To study the sensitivity of the measures to phase information in the signal, phase randomization as well as amplitude adjusted surrogates are also analyzed. We show that the selection of algorithm parameters and the use of normalization are important issues in interpretation and comparison of the results.

EEG sources of noise in intraoperative somatosensory evoked potential monitoring during propofol anesthesia.

Objective: It was hypothesized that somato- sensory evoked potentials can be achieved faster by selective averaging during periods of low spontaneous electroen- cephalographic (EEG) activity. We analyzed the components of EEG that decrease the signal-to-noise ratio of somatosensory evoked potential (SEP) recordings during propofol anesthesia.

Methods: Patient EEGs were recorded with a high sampling frequency during deep anesthesia, when EEGs were in burst suppression.

Comparison of the properties of EEG spindles in sleep and propofol anesthesia.

Electroencephalogram spindle patterns corresponding to two different phenomena-natural sleep and propofol anesthesia-are compared. The spindles are extracted from 5 overnight sleep recordings and 10 recordings of deep propofol anesthesia. Mean frequency, angle of the trend in instant frequency as well as 3 nonlinear parameters-spectral entropy, approximate entropy, and Higuchi fractal dimension- are calculated to characterize the spindle waveforms.