Relationship between approximate entropy and visual inspection of irregularity in the EEG signal, a comparison with spectral entropy.

Background: Several measures have been developed to quantify the change in EEG from wakefulness to deep anaesthesia. Measures of signal complexity or entropy have been popular and even applied in commercial monitors. These measures quantify different features of the signal, however, and may therefore behave in an incomparable way when calculated for standardized EEG patterns.

Sensitive method for determination of protein and cell concentrations based on competitive adsorption to nanoparticles and time-resolved luminescence resonance energy transfer between labeled proteins.

A sensitive mix-and-measure method for the determination of protein and cell concentrations was developed. It is based on the competitive adsorption between the analyte and donor- and acceptor-labeled proteins to carboxylate-modified polystyrene nanoparticles. A high time-resolved luminescence resonance energy transfer (TR-LRET) signal is detected in the absence of the analyte due to the close proximity of the nanoparticle-adsorbed labeled proteins.

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.

Burst suppression during propofol anaesthesia recorded from scalp and subthalamic electrodes: report of three cases.

Background: Measurement of slow EEG activity and burst suppression are the main tasks in monitoring the effects of anaesthestics with EEG, which is often done with commercial univariate indexes such as BIS. The aim of this study was to describe the characteristics of burst suppression EEG during propofol anaesthesia using scalp electrodes and depth electrodes in the subthalamic nucleus. Specifically, we describe the electrical fields of the three EEG patterns we have previously described: the sharp wave, the burst and the spindle.

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.