Early detection of altered brain function can be helpful in preventing the development of serious brain damage. Power spectral analysis of continuous EEG is an established tool in corresponding clinical monitoring. The commonly used EEG power classifiers are based on the power within particular frequency bands. It can be supposed that individually adapted frequency bands allow a more specific monitoring of altered brain function than the commonly used standard EEG frequency bands. In order to test this hypothesis and provide an appropriate signals analysis approach. A hybrid analysis system (HAS) containing variable frequency band power estimators and artificial neural networks (ANNs) was trained with regard to brain function during well-defined states of hemorrhagic hypotension. The aim of the methodical study presented in this article was to investigate whether specific EEG frequency band power parameters can be found by means of this HAS, which enables better detection and classification of moderately reduced brain supply than the classical fixed frequency bands.