Automated detection of respiratory phenotypes during sleep

H. Schneider, S. P. Patil, E. Gladmon, S. Haeussler, M. Wagner, P. L. Smith, A. R. Schwartz

Research output: Contribution to journalConference articlepeer-review

Abstract

We hypothesized that normal individuals can be distinguished on the basis of specific respiratory phenotypes during sleep that determine one's susceptibility to the development of obstructive sleep apnea. To test this hypothesis, methods have been developed to 1.) rapidly assess baseline upper airway and respiratory timing characteristics and compensatory responses in these parameters to experimentally induced upper airway obstruction during sleep in normal individuals, and 2.) automate the detection of the respiratory pattern and the presence of flow limitation during these experimentally induced upper airway obstructions. We demonstrated that: (1) marked variability in the responses to upper airway obstruction exist among normal individuals, and that (2) upper airway collapsibility (critical pressure) is modulated dynamically by a number of reflex neuromuscular responses triggered by breathing through an obstructed upper airway. Moreover, (3) our methods allowed us to assess the relative strength of compensatory neuromuscular responses to upper airway obstruction in normal individuals. Our findings indicate that the normal individual's susceptibility to the development of upper airway obstruction during sleep is determined by the passive upper airway properties and/or by a lack of vigorous compensatory neuromuscular responses.

Original languageEnglish (US)
Pages (from-to)1546-1547
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
StatePublished - Dec 1 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

Keywords

  • Obstructive apnea
  • Respiratory pattern
  • Respiratory phenotypes

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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