Automatic Nonnutritive Suck Waveform Discrimination and Feature Extraction in Preterm Infants.

ABSTRACT: Background and Objective: The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a cross-platform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Met

SUBMITTER: Liao C 

PROVIDER: S-EPMC6378788 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature