Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram

Alexander Neergaard Olesen, Stanislas Chambon, Valentin Thorey, Poul Jennum, Emmanuel Mignot, Helge Bjarup Dissing Sørensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Much attention has been given to automatic sleep staging algorithms in past years, but the detection of discrete events in sleep studies is also crucial for precise characterization of sleep patterns and possible diagnosis of sleep disorders. We propose here a deep learning model for automatic detection and annotation of arousals and leg movements. Both of these are commonly seen during normal sleep, while an excessive amount of either is linked to disrupted sleep patterns, excessive daytime sleepiness impacting quality of life, and various sleep disorders. Our model was trained on 1,485 subjects and tested on 1,000 separate recordings of sleep. We tested two different experimental setups and found optimal arousal detection was attained by including a recurrent neural network module in our default model with a dynamic default event window (F1 = 0.75), while optimal leg movement detection was attained using a static event window (F1 = 0.65). Our work show promise while still allowing for improvements. Specifically, future research will explore the proposed model as a general-purpose sleep analysis model.
Original languageEnglish
Title of host publicationProceedings of 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2019
Pages556-561
ISBN (Print)978-1-5386-1311-5
DOIs
Publication statusPublished - 2019
Event2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society - CityCube Berlin, Berlin, Germany
Duration: 23 Jul 201927 Jul 2019
https://embc.embs.org/2019/

Conference

Conference2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
LocationCityCube Berlin
Country/TerritoryGermany
CityBerlin
Period23/07/201927/07/2019
Internet address

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