The way to eeg-classification: Transition from language of patterns to language of systems

Abstract

An approach is proposed based on identification of systems underlying EEG to reduce the number of descriptors required. Five-minute EEG records were collected from 39 normal subjects in 3 states: eyes closed, fingering beads, eyes open. The algorithm included a spectral analysis, separation of rhythms by a finite memory filter, and autocorrelation analysis of the oscillations and their envelope. Only three oscillatory systems were identified reliably. All of them pertain to the alpha-band: independent frontal and occipital alpha-rhythms, and a mu-rhythm. A division of the subjects into 5 groups has been based on the presence or absence of these systems. Across groups, the mean frequency of the alpha-system was 10.2 Hz, mu-system—10.0Hz. The mean damping decrement equalled. 24 for the occipital alpha system,. 30 for mu. The assumption that rhythms in the alpha-band can be created due to the physiological equivalent of narrow-band filters with stochastic neuronal activity at their input has been confirmed in the majority of cases.

Key Words:

• EEG classification
• alpha- and mu-rhythm
• oscillatory systems identification