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Related Experiment Videos

The Narcotrend monitor.

S Kreuer1, W Wilhelm

  • 1Department of Anaesthesiology and Intensive Care Medicine, University of Saarland, 66421 Homburg/Saar, Germany. sascha.kreuer@uniklinik-saarland.de

Best Practice & Research. Clinical Anaesthesiology
|April 26, 2006
PubMed
Summary
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The Narcotrend monitor uses electroencephalogram (EEG) pattern recognition to assess anaesthesia depth, classifying brain activity into stages A-F. It offers valuable data for monitoring patients during procedures.

Area of Science:

  • Anesthesiology
  • Neuroscience
  • Biomedical Engineering

Background:

  • The Narcotrend is an electroencephalogram (EEG) monitor developed for measuring anaesthesia depth.
  • It has received US Food and Drug Administration approval and is commercially available.
  • The device utilizes pattern recognition of raw EEG signals.

Purpose of the Study:

  • To describe the Narcotrend monitor, its algorithm, and its capabilities in assessing anaesthesia depth.
  • To highlight the information provided by the Narcotrend monitor, including stages, index, and EEG parameters.
  • To note the availability of clinical validation studies, including comparisons with the BIS monitor.

Main Methods:

  • The Narcotrend algorithm classifies raw EEG traces into stages A (awake) to F (burst suppression/electrical silence).

Related Experiment Videos

  • A dimensionless Narcotrend index ranges from 100 (awake) to 0 (electrical silence).
  • Standard electrocardiogram electrodes are used for single- and double-channel EEG signal registration.

    • Main Results:

    • The Narcotrend monitor provides real-time data including Narcotrend stage, index, trend ('cerebrogram'), raw EEG, power spectrum, and derived EEG parameters.
    • The system classifies EEG into distinct stages reflecting anaesthesia depth.
    • Validation studies comparing Narcotrend with the BIS monitor are available.

    Conclusions:

    • The Narcotrend monitor is a comprehensive EEG-based tool for assessing anaesthesia depth.
    • It offers a range of data outputs, including a numerical index and classification stages.
    • Clinical validation supports its use in anaesthesia monitoring.