Artificial intelligence has been advancing in fields including anesthesiology. This scoping
review of the intersection of artificial intelligence and anesthesia research identified and …

The entropic brain hypothesis proposes that within upper and lower limits, after which
consciousness may be lost, the entropy of spontaneous brain activity indexes the …

Investigating changes in brain function induced by mind-altering substances such as LSD is
a powerful method for interrogating and understanding how mind interfaces with brain, by …

EEG-based emotion recognition is a challenging and active research area in affective
computing. We used three-dimensional (arousal, valence and dominance) model of emotion …

Entropy is a powerful tool for the analysis of time series, as it allows describing the
probability distributions of the possible state of a system, and therefore the information …

Background Sleep staging is a critical step in a range of electrophysiological signal
processing pipelines used in clinical routine as well as in sleep research. Although the …

Over the last years, a surge of empirical studies converged on complexity-related measures
as reliable markers of consciousness across many different conditions, such as sleep …

Permutation entropy (PE) has been recently suggested as a novel measure to characterize
the complexity of nonlinear time series. In this paper, we propose a simple method to …

Highlights:► Twelve entropy indices were systematically compared in monitoring depth of
anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in …

The electroencephalogram (EEG) has proven a valuable tool in the study and detection of
epilepsy. This paper investigates for the first time the use of Permutation Entropy (PE) as a …