Robust filters for intensive care monitoring – beyond the running median

dc.contributor.authorFried, Roland
dc.contributor.authorGather, Ursula
dc.contributor.authorSchettlinger, Karen
dc.date.accessioned2006-03-16T15:33:41Z
dc.date.available2006-03-16T15:33:41Z
dc.date.issued2006-03-16T15:33:41Z
dc.description.abstractCurrent 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.en
dc.description.sponsorshipWe gratefully acknowledge the support of the German Research Foundation DFG through the collaborative research centre SFB 475 "Reduction of Complexity for Multivariate Data Structures".de
dc.format.extent332221 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2003/22247
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-14254
dc.language.isoen
dc.subjectCurrent alarm systemen
dc.subjectFilteren
dc.subjectIntensive care unitsen
dc.subjectSignal extractionen
dc.subject.ddc004
dc.titleRobust filters for intensive care monitoring – beyond the running medianen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access

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