[Automatic EEG analysis in the time domain and its possible clinical significance--presentation of a flexible...

The intention of the automatic EEG analysis is to take several EEG characteristics into account and therefore be usable for different applications to quantify events in the EEG. This procedure of analysis is based on the estimation of maxima and minima points within the measured data and the calculation of the wavelength of the half-waves. This is done by correction of the actually measured maxima-minima-points along the t-axis by means of an interpolation technique, and the frequency of half waves are calculated from this solution with an accuracy of half a Hertz. This method was necessary because our equipment allows only a digitalisation rate of 8 ms (Harner, 1977). Using this procedure it is possible to record the frequency distribution, the distribution of amplitudes, and the distribution of steepness as distributions of elementary EEG characteristics. To characterize specified EEG patterns, the EEG data can be classified according to categories of combinations of quantified characteristics. If we consider topological aspects as well there are the following possibilities: 1 element. characteristic--1 EEG channel; 1 element. characteristic--2 or more EEG channels; several element. characteristics--1 EEG channel; several element. characteristics--2 or more channels. There are possibilities of data reduction, exemplified on the distribution of frequencies without taking into account the topological aspects. The above mentioned methods of data reduction are useful for one EEG channel. On the other hand a comparison of the EEG activity in different channels can be done.