[Pattern recognition techniques in sleep polygraphy].

Abstract

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional "adaptive algorithm" allowing individual adjustments to the signal's form and amplitude.

Cite this paper

@article{Jobert1991PatternRT, title={[Pattern recognition techniques in sleep polygraphy].}, author={M. Jobert and W. Scheuler and W. R{\"{o}ske and E. Poiseau and St. Kubicki}, journal={EEG-EMG Zeitschrift für Elektroenzephalographie, Elektromyographie und verwandte Gebiete}, year={1991}, volume={22 3}, pages={178-86} }