| dc.description.abstract | In this research, empirical mode decomposition (EMD) and software, such as Matlab, is used for the analysis of the patients’ electroencephalograms. In order to wipe out the disturbance caused by noise, ensemble empirical mode decomposition (EEMD) is also manipulated in the investigation. Then with the assistance of Fast Fourier Transform, the characteristics of the patients’brain wave in consciousness and anesthesia can be discovered by discussing the difference of the Fourier spectrum of each intrinsic mode function.
The extraction of the characteristic frequency of the Fourier spectrum is divided into two sections, including the frequency of the maximum amplitude and the expected value. The frequency corresponding with the maximum amplitude of the spectrum is the frequency of the maximum amplitude. Besides, moving average is also tried to delete the disturbance caused by noise in the research. According to the analyzed data, the characteristics of the patients’brain wave in consciousness and anesthesia and the filtering effect of EEMD can be compared. In the other section, the convergence of the expected value is calculated and regarded as the characteristics of the brain waves. Subsequently, the possibility graph of the frequency distribution and receiver operating characteristic curve of each IMF are plotted. The IMFs used to identify the characteristics of consciousness and anesthesia can be revealed by exploring features of these graphs. And the identify accuracy of IMF1 is 99 percent.
Finally, the results of these two kinds of characteristic frequency are stated and compared. The filtering effects of EMD and EEMD are also discussed.
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