Automatic Sleep Stage Classification Method based on Transformer-in-Transformer

Moogyeong Kim, Koohong Jung, Wonzoo Chung

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

1 Citation (Scopus)

Abstract

In this paper, a transformer-in-transformer-based sleep stage classification method extracting global information along both time and frequency axes is proposed. Global information along the frequency axis contains important information of the signal, such as harmonics. However, existing deep learning-based sleep staging methods have been focused on capturing global information over time. Inspired by transformer-in-transformer for music information retrieval, which is capable of capturing both time and frequency axes along dependency, we propose to adopt transformer-in-transformer architecture into sequence-to-sequence scheme of automatic sleep staging. Experimental results on SleepEDFX dataset confirm that the proposed method achieves improved performance compared to existing deep learning-based sleep staging methods.

Original languageEnglish
Title of host publication11th International Winter Conference on Brain-Computer Interface, BCI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665464444
DOIs
Publication statusPublished - 2023
Event11th International Winter Conference on Brain-Computer Interface, BCI 2023 - Virtual, Online, Korea, Republic of
Duration: 2023 Feb 202023 Feb 22

Publication series

NameInternational Winter Conference on Brain-Computer Interface, BCI
Volume2023-February
ISSN (Print)2572-7672

Conference

Conference11th International Winter Conference on Brain-Computer Interface, BCI 2023
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period23/2/2023/2/22

Bibliographical note

Funding Information:
This work was partly supported by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2019-0-00079, Artificial Intelligence Graduate School Program(Korea University)), Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00432, Development Of Non-invasive Integrated BCI SW Platform To Control Home Appliance And External Devices By Users Thought Via AR/VR Interface), Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing Users Intentions using Deep Learning), Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2021-0-02068, Artificial Intelligence Innovation Hub), and the BK21 four program through the National Research Foundation (NRF) funded by the Ministry of Education of Korea.

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Automatic Sleep Staging
  • Electroencephalogram (EEG)
  • Transformer-in-Transformer (TNT)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing

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