Standard
Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms. / Olesen, Alexander N.; Jennum, Poul; Peppard, Paul; Mignot, Emmanuel; Sorensen, Helge B.D.
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
Harvard
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.2018.8513080APA
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.2018.8513080Vancouver
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).
https://doi.org/10.1109/EMBC.2018.8513080Author
Olesen, Alexander N. ; Jennum, Poul ; Peppard, Paul ; Mignot, Emmanuel ; Sorensen, Helge B.D. / 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).
Bibtex
@inproceedings{238f0894ab6f46cf96a7b7cf8b2b6af6,
title = "Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms",
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.",
author = "Olesen, {Alexander N.} and Poul Jennum and Paul Peppard and Emmanuel Mignot and Sorensen, {Helge B.D.}",
year = "2018",
doi = "10.1109/EMBC.2018.8513080",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "IEEE",
pages = "3713--3716",
booktitle = "40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018",
note = "40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 ; Conference date: 18-07-2018 Through 21-07-2018",
}
RIS
TY - GEN
T1 - Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms
AU - Olesen, Alexander N.
AU - Jennum, Poul
AU - Peppard, Paul
AU - Mignot, Emmanuel
AU - Sorensen, Helge B.D.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
U2 - 10.1109/EMBC.2018.8513080
DO - 10.1109/EMBC.2018.8513080
M3 - Article in proceedings
C2 - 30440296
AN - SCOPUS:85056649177
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3713
EP - 3716
BT - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PB - IEEE
T2 - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Y2 - 18 July 2018 through 21 July 2018
ER -
