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Python-Embedded Plugin Implementation in ICM+: Novel Tools for Neuromonitoring Time Series Analysis with Examples

Michał M Placek1,2, Abdelhakim Khellaf3,4, Benjamin L Thiemann3,5

  • 1Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. mp963@cam.ac.uk.

Acta Neurochirurgica. Supplement
|April 11, 2021
PubMed
Summary
This summary is machine-generated.

A new Python interface for ICM+ software allows clinical researchers to analyze complex neurocritical care data. This integration enhances analytical capabilities, offering greater flexibility for research using datasets like CENTER-TBI.

Keywords:
Brain monitoringICM+ softwareIntensive careNeuro-monitoringPhysiological signal analysisTBITime series analysisTraumatic brain injury

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Area of Science:

  • Neurocritical care
  • Medical informatics
  • Computational neuroscience

Background:

  • High-resolution physiological datasets in neurocritical care are increasingly available (e.g., CENTER-TBI).
  • Clinical researchers require advanced tools to interrogate these rich datasets.
  • ICM+ is a widely used software for processing bedside monitor data.

Purpose of the Study:

  • To develop a Python scripting interface for the ICM+ calculation engine.
  • To streamline the integration of Python's analytical capabilities into ICM+.
  • To empower clinical researchers with enhanced data analysis tools.

Main Methods:

  • Developed a Python interface for ICM+.
  • Implemented requirements for Python scripts and a descriptor file for function recognition.
  • Included a tool to facilitate the creation of importable Python functions.

Main Results:

  • The Python extension enables users to enrich ICM+ capabilities.
  • Python functions are 15-60% slower than native ICM+ functions, a trade-off for expanded analytical freedom.
  • The interface provides a streamlined method for adding Python scripting functionality.

Conclusions:

  • The ICM+ Python interface offers significant advantages for neurocritical care research.
  • This integration provides unlimited analytical freedom through extensive Python libraries.
  • The tool is efficient and accessible to users with scripting experience.