Some Statistical Methods in Intensive Care Online Monitoring — A Review

  • Roland Fried
  • Ursula Gather
  • Michael Imhoff
  • Marcus Bauer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1933)


Intelligent alarm systems are needed for adequate bedside decision support in critical care. Clinical information systems acquire physiological variables online in short time intervals. To identify complications as well as therapeutic effects procedures for rapid classification of the current state of the patient have to be developed. Detection of characteristic patterns in the data can be accomplished by statistical time series analysis. In view of the high dimension of the data statistical methods for dimension reduction should be used in advance. We discuss the potential of statistical techniques for online monitoring.


Time Series Dimension Reduction Online Monitoring Estimation Period Multivariate Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Roland Fried
    • 1
  • Ursula Gather
    • 1
  • Michael Imhoff
    • 2
  • Marcus Bauer
    • 1
  1. 1.Department of StatisticsUniversity of DortmundDortmundGermany
  2. 2.Surgical DepartmentCommunity Hospital DortmundDortmundGermany

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