Automatic event detection of REM sleep without atonia from polysomnography signals using deep neural networks

Phillip Wallis, Daniel Yaeger, Alexander Kain, Xubo Song, Miranda Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Rapid eye movement (REM) sleep behavior disorder (RBD) is a sleep disorder that features loss of atonia, or REM sleep without atonia (RSWA). RBD and RSWA are early manifestations of degenerative neurological diseases such as Parkinson's and Lewy Body Dementia. Accurate diagnosis of RBD is crucial for proper treatment planning and is invaluable for early detection of these neurodegenerative diseases. The current gold standard diagnosis of RSWA is through manual visual scoring by a clinician, which is labor-intensive, costly and error-prone. We develop a novel, efficient, and objective method using deep learning to detect RSWA events from polysomnography signals using a large cohort of 692 patients. Unlike previous automated methods that generate only a binary patient diagnosis, our method detects the location and class of all RSWA events. This finer-grained analysis forms the basis for subsequent diagnosis, and allows the quantification of event duration and frequency which in turn can help quantify disease load.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4112-4116
Number of pages5
ISBN (Electronic)9781509066315
DOIs
StatePublished - May 2020
Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: May 4 2020May 8 2020

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Country/TerritorySpain
CityBarcelona
Period5/4/205/8/20

Keywords

  • Deep Learning
  • Machine Learning
  • Polysomnography (PSG)
  • REM sleep without atonia (RSWA)
  • Rapid eye movement sleep behavior disorder (RBD)

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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