Temporal Convolutional Network-based Multi-View Sleep Staging

Koohong Jung, Wonzoo Chung

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


In this paper, we propose a novel approach for multi-view sleep staging using Temporal Convolutional Networks (TCNs). Our method effectively processes both time and time-frequency domain representations by incorporating intra and inter-epoch level layers of TCNs. Unlike previous methods that heavily relied on a single input type, such as time-domain signals or time-frequency representations, our approach tackles the challenge of simultaneously utilizing both domains compared to using only one as input. While many existing automated sleep staging methods employ recurrent neural networks (RNNs) to capture sequential information at intra and inter-epoch levels, there are potential limitations associated with RNNs, such as gradient vanishing or exploding, and computational complexity. Therefore, we adopt a TCN-based architecture to effectively capture intra and inter-epoch dependencies in 30-second EEG signals. Moreover, we propose a novel gradient blending method that considers both validation and training losses at recent and current timesteps. This method is designed to facilitate training and achieve enhanced performance by emphasizing on the recent trend of the training process. On numerical simulation results, conducted on the SleepEDF-20 and DRM-Sub dataset demonstrate that our proposed method outperforms the existing automated sleep staging methods.

Original languageEnglish
Title of host publication12th International Winter Conference on Brain-Computer Interface, BCI 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350309430
Publication statusPublished - 2024
Event12th International Winter Conference on Brain-Computer Interface, BCI 2024 - Gangwon, Korea, Republic of
Duration: 2024 Feb 262024 Feb 28

Publication series

NameInternational Winter Conference on Brain-Computer Interface, BCI
ISSN (Print)2572-7672


Conference12th International Winter Conference on Brain-Computer Interface, BCI 2024
Country/TerritoryKorea, Republic of

Bibliographical note

Publisher Copyright:
© 2024 IEEE.


  • Brain-Computer Interface (BCI)
  • Electroencephalogram (EEG)
  • Sleep Stage Classification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing


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