ORDER PATTERNS RECURRENCE ANALYSIS OF ELECTROENCEPHALOGRAM DURING SEVOFLURANE ANESTHESIA

Abstract

Characterizing the brain activity during anesthesia is considered a major challenge for researchers. The concentration-relevant effect of the sevoflurane is evaluated on EEG signals collected from 19 patients during a proscribed induction and recovery setup. Recurrence Quantification Analysis based on order patterns is employed to provide an index named order laminarity (OLAM) to evaluate changes in the neuronal system. This index computes the activity of a part of brain without considering the number or dynamical nature of the individual sources and signifies segments staying in the same phase space region for a short time. Pharmacokinetic-pharmacodynamic modeling and statistical features are used to assess the effectiveness of the OLAM index compared with response entropy index as implemented in the commercial Datex-Ohmeda Module. Both methods track the overall changes in EEG. However, the OLAM can be proficiently computed and is artifact resistant (standard deviation of 0.016 for OLAM relative to 0.02 for response entropy index). This measure as a neurophysiologic correlation of general anesthesia also reacts quicker to alternations in EEG signals during induction and correlates more powerfully with drug concentration (The prediction probability of 0.89 for OLAM is proportionate to 0.83 for response entropy). This examination exemplifies a crucial translational phase from the neuroscience of consciousness to more intricate monitoring of anesthetic effects in patients.