On the use of neural network techniques to analyze sleep EEG dataSecond communication: Training of evolutionary optimized neural networks on the basis of multiple subjects data and the application of context rules according to Rechtschaffen and KalesÜber den Nutzen Neuronaler Netzwerk-Techniken zur Analyse von Schalaf-EEG-DatenTeil II: Training von evolutionär optimierten neuronalen Netzwerken und Applikation von Kontext-Regeln auf der Basis der Regeln von Rechtschaffen und Kales

被引：0
作者：
R. Baumgart-Schmitt
R. Eilers
W. M. Herrmann
机构：
[1] Free University of Berlin,Department of Electrical Engineering, SIT (Schmalkalden Institute of Technology)
[2] Free University of Berlin,Interdisciplinary Sleep Clinic, Department of Psychiatry, Benjamin Franklin Hospital
[3] PAREXEL International Corporation,Labor für Klinische Psychophysiologie
[4] Psychiatrische Klinik FUB,undefined
来源：
Somnologie - Zeitschrift für Schlafforschung und Schlafmedizin | 1997年 / 1卷 / 4期
关键词：
automated sleep stage scoring; neural network classification; Automatische Schlafstadien-Analyse; neuronale Netzwerk Klassifikation;
D O I：
10.1007/s11818-997-0031-3
中图分类号：
学科分类号：
摘要：
The system SASCIA (Sleep Analysis System to Challenge Innovative Artificial Networks) is applied to automate the sleep stage scoring. The information content of only one EEG channel (C4-A2) was use. The results of 16 nights from 9 different subjects were used to test the performance of the system.
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收藏
页码：171 / 183
页数：12
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