Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms

Alexander N. Olesen; Poul Jennum; Paul Peppard; Emmanuel Mignot; Helge B.D. Sorensen

doi:10.1109/EMBC.2018.8513080

Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms

Alexander N. Olesen^*, Poul Jennum, Paul Peppard, Emmanuel Mignot, Helge B.D. Sorensen

^*Corresponding author for this work

Department of Clinical Medicine

10 Citations (Scopus)

Abstract

We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50 convolutional layers before subsequent classification into one of five sleep stages. Three model configurations were trained on 1850 polysomnogram recordings and subsequently tested on 230 independent recordings. Our best performing model yielded an accuracy of 84.1% and a Cohen's kappa of 0.746, improving on previous reported results by other groups also using only raw polysomnogram data. Most errors were made on non-REM stage 1 and 3 decisions, errors likely resulting from the definition of these stages. Further testing on independent cohorts is needed to verify performance for clinical use.

Original language	English
Title of host publication	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Number of pages	4
Publisher	IEEE
Publication date	2018
Pages	3713-3716
Article number	8513080
ISBN (Electronic)	978-1-5386-3646-6
DOIs	https://doi.org/10.1109/EMBC.2018.8513080
Publication status	Published - 2018
Event	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States Duration: 18 Jul 2018 → 21 Jul 2018

Conference

Conference	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/Territory	United States
City	Honolulu
Period	18/07/2018 → 21/07/2018

Series	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2018-July
ISSN	1557-170X

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10.1109/EMBC.2018.8513080

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Olesen, A. N., Jennum, P., Peppard, P., Mignot, E., & Sorensen, H. B. D. (2018). Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 3713-3716). [8513080] IEEE. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS Vol. 2018-July https://doi.org/10.1109/EMBC.2018.8513080

Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. / Olesen, Alexander N.; Jennum, Poul; Peppard, Paul et al.

40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. IEEE, 2018. p. 3713-3716 8513080 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Olesen, AN, Jennum, P, Peppard, P, Mignot, E & Sorensen, HBD 2018, Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8513080, IEEE, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2018-July, pp. 3713-3716, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 18/07/2018. https://doi.org/10.1109/EMBC.2018.8513080

Olesen AN, Jennum P, Peppard P, Mignot E, Sorensen HBD. Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. IEEE. 2018. p. 3713-3716. 8513080. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Vol. 2018-July). doi: 10.1109/EMBC.2018.8513080

Olesen, Alexander N. ; Jennum, Poul ; Peppard, Paul et al. / Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. IEEE, 2018. pp. 3713-3716 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Vol. 2018-July).

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Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms

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