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Robust Filters for Intensive Care Monitoring: Beyond the Running Median

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  • Schettlinger, Karen
  • Fried, Roland
  • Gather, Ursula

Abstract

Current alarm systems on intensive care units create a very high rate of false positive alarms because most of them simply compare the physiological measurements to fixed thresholds. An improvement can be expected when the actual measurements are replaced by smoothed estimates of the underlying signal. However, classical filtering procedures are not appropriate for signal extraction as standard assumptions, like stationarity, do no hold here: the measured time series often show long periods without change, but also upward or downward trends, sudden shifts and numerous large measurement artefacts. Alternative approaches are needed to extract the relevant information from the data, i.e. the underlying signal of the monitored variables and the relevant patterns of change, like abrupt shifts and trends. This article reviews recent research on filter based online signal extraction methods which are designed for application in intensive care.

Suggested Citation

  • Schettlinger, Karen & Fried, Roland & Gather, Ursula, 2006. "Robust Filters for Intensive Care Monitoring: Beyond the Running Median," Technical Reports 2006,23, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200623
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    References listed on IDEAS

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    1. Ursula Gather & Karen Schettlinger & Roland Fried, 2006. "Online signal extraction by robust linear regression," Computational Statistics, Springer, vol. 21(1), pages 33-51, March.
    2. P.J. Rousseeuw & A.M. Leroy, 1988. "A robust scale estimator based on the shortest half," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 42(2), pages 103-116, June.
    3. Fried, Roland & Bernholt, Thorsten & Gather, Ursula, 2006. "Repeated median and hybrid filters," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2313-2338, May.
    4. Struyf, Anja J. & Rousseeuw, Peter J., 1999. "Halfspace Depth and Regression Depth Characterize the Empirical Distribution," Journal of Multivariate Analysis, Elsevier, vol. 69(1), pages 135-153, April.
    5. Gather, Ursula & Einbeck, Jochen & Fried, Roland, 2005. "Weighted Repeated Median Smoothing and Filtering," Technical Reports 2005,33, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Fried, Roland & Gather, Ursula, 2004. "Methods and algorithms for robust filtering," Technical Reports 2004,44, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    7. Bernholt, Thorsten & Fried, Roland & Gather, Ursula & Wegner, Ingo, 2004. "Modified repeated median filters," Technical Reports 2004,46, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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