Channel-Aware Self-Supervised Learning for EEG-based BCI

Sangmin Jo, Jaehyun Jeon, Seungwoo Jeong, Heung Il Suk

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


Electroencephalography (EEG) can record brain activity in a non-invasive way, but it is expensive and has high inter-and intra-subject variability. Recent research on EEG analysis using deep learning has shown great performance in dealing with this problem, but there is still the issue of heterogeneity. In this work, we propose a novel self-supervised learning method that can extract robust signal representations of EEG to solve the mentioned problem. To model the paradigm in which different channels exist, we devise a channel-aware encoder. In the downstream task, fine-tuning was performed by adding spatial convolution to consider channel information in the feature obtained by a single channel encoder. For the validity of our proposed framework, we conduct experiments using two public datasets with different paradigms, i.e., sleep staging classification and seizure detection. Further, we compare the proposed method to other comparable 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
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
ISSN (Print)2572-7672


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

Bibliographical note

Publisher Copyright:
© 2023 IEEE.


  • Electroencephalogram
  • Seizure Detection
  • Self-Supervised Learning
  • Sleep Staging Classification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing


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