Subject-Independent Brain-Computer Interfaces: A Comparative Study of Attention Mechanism-Driven Deep Learning Models

Aigerim Keutayeva, Berdakh Abibullaev

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

1 Citation (Scopus)

Abstract

This research examines the employment of attention mechanism driven deep learning models for building subject-independent Brain-Computer Interfaces (BCIs). The research evaluated three different attention models using the Leave-One-Subject-Out cross-validation method. The results showed that the Hybrid Temporal CNN and ViT model performed well on the BCI competition IV 2a dataset, achieving the highest average accuracy and outperforming other models for 5 out of 9 subjects. However, this model did not perform the best on the BCI competition IV 2b dataset when compared to other methods. One of the challenges faced was the limited size of the data, especially for transformer models that require large amounts of data, which affected the performance variability between datasets. This study highlights a beneficial approach to designing BCIs, combining attention mechanisms with deep learning to extract important inter-subject features from EEG data while filtering out irrelevant signals.

Original languageEnglish
Title of host publicationIntelligent Human Computer Interaction - 15th International Conference, IHCI 2023, Revised Selected Papers
EditorsBong Jun Choi, Dhananjay Singh, Uma Shanker Tiwary, Wan-Young Chung
PublisherSpringer Science and Business Media Deutschland GmbH
Pages245-254
Number of pages10
ISBN (Print)9783031538261
DOIs
Publication statusPublished - 2024
Event15th International Conference on Intelligent Human Computer Interaction, IHCI 2023 - Daegu, Korea, Republic of
Duration: Nov 8 2023Nov 10 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14531 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Intelligent Human Computer Interaction, IHCI 2023
Country/TerritoryKorea, Republic of
CityDaegu
Period11/8/2311/10/23

Keywords

  • Attention Mechanism
  • Brain-Computer Interface (BCI)
  • Deep Learning (DL)
  • Motor Imagery (MI)
  • Vision Transformers (VT)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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