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Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods
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Frequency of flow limitation using airflow shape.

Dwayne L Mann1,2,3, Thomas Georgeson1,4, Shane A Landry3,5

  • 1School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.

Sleep
|July 9, 2021
PubMed
Summary
This summary is machine-generated.

Quantifying sleep-disordered breathing flow limitation is challenging. This study introduces an automated method to measure flow limitation frequency, revealing its independence from obstructive sleep apnea severity and its prevalence during sleep events.

Keywords:
airflow obstructionautomatedclassificationdiaphragm EMGinspiratory flow limitationphenotypepolysomnographyupper airway resistance syndrome

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Area of Science:

  • Sleep Medicine
  • Respiratory Physiology
  • Biomedical Engineering

Background:

  • Flow limitation during sleep has health risks independent of obstructive sleep apnea (OSA) severity.
  • Quantifying this flow limitation is difficult, hindering clinical assessment.

Purpose of the Study:

  • To develop and validate an automated method for quantifying flow limitation frequency during sleep.
  • To investigate the relationship between flow limitation, OSA severity (apnea-hypopnea index, AHI), and ventilatory drive.

Main Methods:

  • A library of 117,871 breaths from 40 participants was classified for flow limitation.
  • An ordinal regression model was trained using airflow and physiological signals to quantify flow limitation.
  • The model's performance was evaluated against visual scoring for breath-by-breath agreement and overnight frequency.

Main Results:

  • The automated method demonstrated good agreement (Cohen's ƙ = 0.572) and minimal error (R2 = 0.86) in quantifying flow limitation frequency.
  • Flow limitation frequency was largely independent of AHI (R2 = 0.16) and showed wide individual variation.
  • Flow limitation was prevalent during arousals (40%) and stable breathing (58%) and associated with elevated ventilatory drive.

Conclusions:

  • An automated method for quantifying flow limitation frequency during sleep has been developed and validated.
  • Flow limitation frequency is an important metric, independent of AHI, that varies significantly between individuals.
  • The findings highlight the prevalence of flow limitation during various sleep stages and its association with increased ventilatory drive.