# Monitoring Depth of Anesthesia

Chapter

## Abstract

This chapter examines the use of complexity analysis, approximate entropy, wavelet transforms, artificial neural networks, fuzzy logic, and neuro-fuzzy method (adaptive network-based fuzzy inference systems) to determine the depth of anesthesia (DOA) of a patient by analyzing mid-latency auditory evoked potentials (MLAEP) and electroencephalograms (EEG). Comparisons are made of the success and computational efficiency of each technique using the data of experimental dogs with different anesthetic modalities.

## Keywords

Artificial Neural Network Fuzzy Logic Mean Arterial Pressure Fuzzy Inference System Adaptive Network Base Fuzzy Inference System
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