title: [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.
authors.affiliation: Abteilung für Klinische Neurophysiologie, Freie Universität Berlin.
authors.forename: M
authors.initials: M
authors.lastname: Jobert
authors.forename: W
authors.initials: W
authors.lastname: Scheuler
authors.forename: W
authors.initials: W
authors.lastname: Röske
authors.forename: E
authors.initials: E
authors.lastname: Poiseau
authors.forename: S
authors.initials: S
authors.lastname: Kubicki
mesh_terms: D000465:Algorithms; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008838:Microcomputers; D010363:Pattern Recognition, Automated; D012890:Sleep / Q000502:physiology*
vernacular_title: Verfahren zur Mustererkennung in der Schlaf-Polygraphie.