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The concept of entropy, originally derived from thermodynamics, has been successfully applied to EEG analysis. Various entropy algorithms have been used in clinical studies, but until now a commercially available monitor exists only for spectral entropy. By calculating two distinct values for the EEG dominated part of the spectrum (state entropy, SE) and the total spectrum (response entropy, RE), the M-Entropy module claims to provide useful information regarding the cortical state of the patient as well as an indirect measure of adequacy of analgesia. Generally, entropy has been studied for quantification of anaesthetic drug effect for various GABA-ergic i.v. induction agents and volatile anaesthetics like propofol and sevoflurane and overall was found comparable to the current clinical gold standard bispectral index (BIS). Entropy guidance may not be used during ketamine or nitrous oxide administration, since there is no reliable correlation to the patient''s state of consciousness. The usefulness of RE as a surrogate for increased EMG activity due to painful stimulation has not been proven so far. [Copyright &y& Elsevier]

The relationship between the electro-encephalographic (EEG) alpha and beta oscillations in the resting condition was investigated in the study. EEGs were recorded in 33 subjects, and alpha (7.5-12.5 Hz) and beta (15-25 Hz) oscillations were extracted with the use of a modified wavelet transform. Power, peak frequency and phase synchronisation were evaluated for both types of oscillation. The average beta-alpha peak frequency ratio was about 1.9-2.0 for all electrode derivations. The peak frequency of beta activity was within 70-90 % of the 95 % confidence interval of twice the alpha frequency. A significant (p < 0.05) linear regression was found between beta and alpha power in all derivations in 32 subjects, with the slope of the regression line being approximately 0.3. There was no significant difference in the slope of the line in different electrode locations, although the power correlation was strongest in the occipital locations where alpha and beta oscillations had the largest power. A significant 1:2 phase synchronisation was present between the alpha and beta oscillations, with a phase lag of about pi/2 in all electrode derivations. The strong frequency relationship between the resting beta and alpha oscillations suggests that they are generated by a common mechanism. Power and phase relationships were weaker, suggesting that these properties can be modulated by additional mechanisms as well as be influenced by noise. A careful distinction between alpha-dependent and alpha-independent beta activity should be considered when making statements about the possible significance of genuine beta activity in different neurophysiological mechanisms. [ABSTRACT FROM AUTHOR]