A Method for Quantifying the Depth of Anesthesia of Rats Based on Physiological Signal Model

Abstract

Measuring the depth of anesthesia using electroencephalogram (EEG) is an important and challenging task. Although various methods using EEG have been proposed, these algorithms quantify the depth of anesthesia without any physiological models. In this paper, a method to quantify the depth of anesthesia as well as a signal model that describes the changes in EEG during anesthesia is presented. The signal model is composed of numerous electrical signal sources and low-pass filters which model the microscopic signal from neurons and the electrical characteristics of the brain, respectively. Using the signal model, EEG is simulated as a summation of lowpass filtered impulse trains. The signal model suggests that the features of EEG change due to the decrease of the percent of pyramidal cells in the active state during anesthesia. Based on the signal model, an index for the depth of anesthesia, referred to as cortical activity index (CAI), is proposed. For the verification of the method, EEG signals from anesthetized rats are obtained and analyzed to evaluate the level of consciousness. The measurement results indicated that the proposed index, CAI, has achieves high stability over wide range of the depth of anesthesia. Moreover, it shows high correlation with other indexes such as modified detrend moving average (MDMA) and the WAVcns index. Based on the experimental results, CAI could be considered as a promising method to quantify depth of anesthesia with the plausible physiological signal model.