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

Moogyeong Kim; Koohong Jung; Wonzoo Chung

doi:10.1109/BCI57258.2023.10078607

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

Moogyeong Kim, Koohong Jung, Wonzoo Chung

Department of Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 language	English
Title of host publication	11th International Winter Conference on Brain-Computer Interface, BCI 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665464444
DOIs	https://doi.org/10.1109/BCI57258.2023.10078607
Publication status	Published - 2023
Event	11th International Winter Conference on Brain-Computer Interface, BCI 2023 - Virtual, Online, Korea, Republic of Duration: 2023 Feb 20 → 2023 Feb 22

Publication series

Name	International Winter Conference on Brain-Computer Interface, BCI
Volume	2023-February
ISSN (Print)	2572-7672

Conference

Conference	11th International Winter Conference on Brain-Computer Interface, BCI 2023
Country/Territory	Korea, Republic of
City	Virtual, Online
Period	23/2/20 → 23/2/22

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

Access to Document

10.1109/BCI57258.2023.10078607

Cite this

Kim, M., Jung, K., & Chung, W. (2023). Automatic Sleep Stage Classification Method based on Transformer-in-Transformer. In 11th International Winter Conference on Brain-Computer Interface, BCI 2023 (International Winter Conference on Brain-Computer Interface, BCI; Vol. 2023-February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCI57258.2023.10078607

Automatic Sleep Stage Classification Method based on Transformer-in-Transformer. / Kim, Moogyeong; Jung, Koohong; Chung, Wonzoo.
11th International Winter Conference on Brain-Computer Interface, BCI 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (International Winter Conference on Brain-Computer Interface, BCI; Vol. 2023-February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, M, Jung, K & Chung, W 2023, Automatic Sleep Stage Classification Method based on Transformer-in-Transformer. in 11th International Winter Conference on Brain-Computer Interface, BCI 2023. International Winter Conference on Brain-Computer Interface, BCI, vol. 2023-February, Institute of Electrical and Electronics Engineers Inc., 11th International Winter Conference on Brain-Computer Interface, BCI 2023, Virtual, Online, Korea, Republic of, 23/2/20. https://doi.org/10.1109/BCI57258.2023.10078607

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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.",

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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: {\textcopyright} 2023 IEEE.; 11th International Winter Conference on Brain-Computer Interface, BCI 2023 ; Conference date: 20-02-2023 Through 22-02-2023",

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this