Deep learning applied to polysomnography to predict blood pressure in obstructive sleep apnea and obesity hypoventilation: a proof-of-concept study.

Journal: Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
Published Date: Oct 15, 2020

Abstract

STUDY OBJECTIVES: Nocturnal blood pressure (BP) profile shows characteristic abnormalities in OSA, namely acute postapnea BP surges and nondipping BP. These abnormal BP profiles provide prognostic clues indicating increased cardiovascular disease risk. We developed a deep neural network model to perform computerized analysis of polysomnography data and predict nocturnal BP profile.

Authors

  • Bharati Prasad
    Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.
  • Chirag Agarwal
    Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, Illinois.
  • Elan Schonfeld
    Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, Illinois.
  • Dan Schonfeld
    Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, Illinois.
  • Babak Mokhlesi
    Section of Pulmonary and Critical Care, Sleep Disorders Center, University of Chicago, Chicago, Illinois.

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