NEURAL: quantitative features for newborn EEG using Matlab

Background: For newborn infants in critical care, continuous monitoring of brain function can help identify infants at-risk of brain injury. Quantitative features allow a consistent and reproducible approach to EEG analysis, but only when all implementation aspects are clearly defined. Methods: We detail quantitative features frequently used in neonatal EEG analysis and present a Matlab software package together with exact implementation details for all features. The feature set includes stationary features that capture amplitude and frequency characteristics and features of inter-hemispheric connectivity. The software, a Neonatal Eeg featURe set in mAtLab (NEURAL), is open source and freely available. The software also includes a pre-processing stage with a basic artefact removal procedure. Conclusions: NEURAL provides a common platform for quantitative analysis of neonatal EEG. This will support reproducible research and enable comparisons across independent studies. These features present summary measures of the EEG that can also be used in automated methods to determine brain development and health of the newborn in critical care.

• Publication year

  2017

• Venue

  arXiv: Medical Physics

• Publication date

  2017-04-19

• Fields of study

  Biology, Physics, Computer Science, Mathematics, Medicine

• Identifiers
  arXiv 1704.05694
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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