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

Bharati Prasad | Zendy; Chirag Agarwal | Zendy; Elan Schonfeld | Zendy; Dan Schonfeld | Zendy; Babak Mokhlesi | Zendy

Open Access

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

Author(s) -

Bharati Prasad,

Chirag Agarwal,

Elan Schonfeld,

Dan Schonfeld,

Babak Mokhlesi

Publication year - 2020

Publication title -

journal of clinical sleep medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.529

H-Index - 92

eISSN - 1550-9397

pISSN - 1550-9389

DOI - 10.5664/jcsm.8608

Subject(s) - polysomnography , medicine , cardiology , obstructive sleep apnea , blood pressure , apnea , diastole

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.

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