On-line segmentation algorithm for continuously monitored data in intensive care units.

Sylvie Charbonnier; Guillaume Becq; Loic Biot

doi:10.1109/tbme.2003.821012

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PubMed · 15000379

On-line segmentation algorithm for continuously monitored data in intensive care units.

Sylvie Charbonnier·Guillaume Becq·Loic Biot

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Abstract

An on-line segmentation algorithm is presented in this paper. It is developed to preprocess data describing the patient's state, sampled at high frequencies in intensive care units, with a further purpose of alarm filtering. The algorithm splits the signal monitored into line segments--continuous or discontinuous--of various lengths and determines on-line when a new segment must be calculated. The delay of detection of a new line segment depends on the importance of the change: the more important the change, the quicker the detection. The linear segments are a correct approximation of the structure of the signal. They emphasise steady-states, level changes and trends occurring on the data. The information returned by the algorithm, which is the time at which the segment begins, its ordinate and its slope, is sufficient to completely reconstruct the filtered signal. This makes the algorithm an interesting tool to provide a processed time history record of the monitored variable. It can also be used to extract on-line information on the signal, such as its trend, in the short or long term.

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Algorithms Artifacts Critical Care Diagnosis, Computer-Assisted Expert Systems Humans Intensive Care Units Monitoring, Physiologic Risk Assessment Safety Safety Management Signal Processing, Computer-Assisted Systems Integration Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study

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Sylvie Charbonnier, Guillaume Becq, Loic Biot. 2004. On-line segmentation algorithm for continuously monitored data in intensive care units.. https://doi.org/10.1109/tbme.2003.821012

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