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Statistical methods in intensive care online monitoring

Author

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  • Fried, Roland
  • Gather, Ursula
  • Imhoff, Michael
  • Bauer, Marcus

Abstract

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.

Suggested Citation

  • Fried, Roland & Gather, Ursula & Imhoff, Michael & Bauer, Marcus, 2000. "Statistical methods in intensive care online monitoring," Technical Reports 2000,33, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200033
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    1. Fried, Roland & Gather, Ursula & Imhoff, Michael, 2001. "Pattern recognition in intensive care online monitoring," Technical Reports 2001,15, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

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