Analysis of wake/sleep EEG with competing experts

J. Kohlmorgen, K. R. Müller, J. Rittweger, K. Pawelzik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


An analysis of physiological wake/sleep data is presented. We apply a recent method for the analysis of nonstationary time series with multiple operating modes. In particular, it is possible to detect and to model a switching of the dynamics and also a less abrupt, time consuming drift from one mode to another. This is achieved by an unsupervised algorithm that segments the data according to inherent modes, and a subsequent search through the space of possible drifts. The application to wake/sleep data demonstrates that analysis and modeling of real-world time series can be improved when the drift paradigm is taken into account. In the case of wake/sleep data, we hope to gain more insight into the physiological processes that are involved in the transition from wake to sleep.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings
EditorsWulfram Gerstner, Alain Germond, Martin Hasler, Jean-Daniel Nicoud
PublisherSpringer Verlag
Number of pages6
ISBN (Print)3540636315, 9783540636311
Publication statusPublished - 1997
Externally publishedYes
Event7th International Conference on Artificial Neural Networks, ICANN 1997 - Lausanne, Switzerland
Duration: 1997 Oct 81997 Oct 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th International Conference on Artificial Neural Networks, ICANN 1997

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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