[Pattern recognition techniques in sleep polygraphy].
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.
Jobert
M
M
Abteilung für Klinische Neurophysiologie, Freie Universität Berlin.
Scheuler
W
W
Röske
W
W
Poiseau
E
E
Kubicki
S
S
D000465:Algorithms; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008838:Microcomputers; D010363:Pattern Recognition, Automated; D012890:Sleep / Q000502:physiology*
Verfahren zur Mustererkennung in der Schlaf-Polygraphie.