文件列表:

sim_eeg.m (2142, 2001-09-12)
eeg_seg.m (1991, 2001-09-12)
eeg_demo.m (1194, 2001-09-14)

Author: Dr. Reda Regab Gharieb Reference: R. R. Gharieb and A. Cichocki, "Segmentation and tracking of the electo-encephalogram signal using an adaptive recursive bandpass filter," Medical & Biological Engineering & Computing, IFMBE-2001, vol. 39, pp. 237-248. This package contains the following files: README This file eeg_demo.m Matlab m-file This Demo program is to simulate different segments of EEG signal and to online track theses segments. sim_eeg.m Matlab m-file This is a function using linear modeling for generating an eeg wave specified by the user. eeg_seg.m Matlab m-file This makes segmentation of eeg signal based on the center frequency of each segment. HOW TO RUN This EEG Demo program is to simulate different segments of EEG signal and to online track theses segments. For the simulation, you need Matlab and its Signal Processing Toolbox. 1. Type "eeg_demo" at Matlab command line. You can see demonstration of segmentation of simulated EEG signal. 2. Changing some parameters in eeg_demo.m, you can obtain other results. You can also apply eeg_seg.m to your own data. This m-file calls next two functions and carrys out demonstration. This Demo program is to simulate different segments of EEG signal and to online track theses segments. First, it generates an eeg signal that consists of different segments (e.g. alpha wave, beta wave ....) using sim_eeg function. In the upper figure, the signal is presented. Next, using the matlab specgram function, it represents the spectrogram of the signal in the middle figure. Next, it calculates our segmenting function for tracking the eeg segments and represents the function in the lower figure. We can track the eeg segments by the spectrogram, but our segmenting function represents the segmentation more clearly and is easier to use because it is a scalar function. This is a function using linear modeling for generating an eeg wave specified by the user. You can use both MA model and ARMA model. For usage, please use help command in Matlab. This makes segmentation of eeg signal based on the center frequency of each segment. The function uses an adaptive bandpass filter; the adaptive filter is implemented as a 4th order Butterworth filter; the adaptive filter needs only one coefficient to be updated. The center frequency of the eeg segment is proportional to this adaptive coefficient. For usage, please use help command in Matlab.

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