Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 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.

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The categories of this paper are: eess
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The categories of this paper are: solv-int
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The categories of this paper are: patt-sol
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The categories of this paper are: funct-an
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The categories of this paper are: acc-phys
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: supr-con