An Analysis of MLAEP Based on Wavelet Transformation
Yu Zhang · 2001
Electroencephalogram(EEG) has become the main method of monitoring the depth of anesthesia in modern clinic anesthesiology, and the study of middle latency auditory evoked potentials(MLAEP) has been widely supplied. In this paper, wavelet transformation on MLAEP with Daubechies orthonomal bases of compactly supported wavelets has been made, then the sequential floating forward search method was used for feature selection,and finally the artifical neural network was used as a pattern classifier . The simulation results have shown that the combination of wavelet transformation and feature selection was effective in MLAEP analysis.