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EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb 1989 Jun;20(2):67-75
Strategies of data reduction in computer-assisted EEG analysis in the time
domain--measurement of theoretical aspects and redundancy relations within and between various strategies of data reduction
Spiel G, Spiel C, Benninger F.
The enormous amount of data after performing computer assisted EEG-analysis makes necessary reduction methods. Different strategies have been proposed.
Traditionally the distribution of frequencies is shown by using frequency bands.
The aim of this paper is to compare different strategies of data reduction regarding frequency distribution and to discuss results concerning validity.
Three data reduction methods and their mutual relations will be discussed. The classification with regard to frequency bands, the computation of quartils of
the frequency spectrum and the search for prominent frequencies. It will be shown wether or not calculated values are redundant and reflect identical
information (latent dimensions).
EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb 1986 Mar;17(1):7-10
Demonstration of an interpolation method for determining approximate maximum
and minimum points as a prerequisite for EEG analysis in the time domain using computers with limited memory capacity
Spiel G, Kundi M, Benninger F.
The EEG analysis in the time domain provides several advantages compared to the
power spectra analysis, based on a FFT. There is the possibility to
differentiate frequency, amplitude and other elementary characteristics of the
wave form. This technique of EEG analysis is based on the definition of distinct
characteristics of the wave form. Problems for calculating the frequency distribution arise--according to Harner, 1977--due to the fact, that the
digitalization rate has to be very fast to reach an adequate resolution. On the other hand a high digitalization rate of 5 ms or below produces problems
concerning the limited memory capacity of laboratory computers, especially if more than one derivation should be analysed simultaneously, to make further
topological analyses possible. Three procedures of EEG analysis to calculate frequency distributions are shown, two of them are based on an interpolation
technique to calculate adjusted minima-maxima. The results of these procedures using two different digitalization rates, were compared and discussed to respect
similarity of resulting frequency distributions.
EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb 1986 Mar;17(1):2-6
Data display and reduction in computer-assisted EEG analysis in the time domain
Spiel G, Kundi M, Benninger F.
Analysis of EEG frequency spectra leads in two fields to problems demanding optimal data reduction methods: especially if topological aspects have to be
considered, it is likely that the rather limited memory capacity of laboratory computer systems will be exceeded; furthermore severe methodological problems
arise in statistical analysis of combined data sets, including frequency spectra, other physiological, and non-physiological data. Three data reduction
methods are discussed: the classification with respect to frequency bands, the search for prominent frequencies, and the computation of quartiles of the
frequency spectra. There is some evidence in favour of the method of prominent
frequencies. This method seems to preserve much of the differential information of the frequency spectra.
Padiatr Padol 1986;21(3):221-31
Automatic EEG analysis in the time domain and its possible clinical significance--presentation of a flexible software package
Spiel G, Benninger F.
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.