Lateralization of alpha oscillation under preparation Lead to Efficiency of Motor Imagery: Related with Performance of Classification

Seho Lee, Choel Hui Lee, Hakseung Kim, Dong Joo Kim

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

2 Citations (Scopus)

Abstract

Electroencephalography (EEG) is a primary modality for estimating user intention in the brain-computer interface (BCI). In particular, BCI has been widely used to detect the intention of users in motor imagery (MI)-based tasks. Although the MI classification accuracy has been largely enhanced from previous efforts, MI-BCI studies have focused on extracting features only during MI tasks, not during the preparatory phases. The increment of alpha band power is induced by performing a task with attention. This study proposes a n approach for increasing MI-BCI performance by analyzing brain state in preparatory before the task. EEG recordings of nine healthy subjects from the open BCI dataset were investigated. The alpha lateralization index (ALI) was calculated for each trial and high ALI trials were utilized for learning lateralization-based model. MI classification accuracy using the lateralization-based model marked high performance (median accuracy = 63.2 %; interquartile range (IQR) = 50.0% - 54.8%) than the total trial-based approach (median accuracy = 52.0%; IQR = 50.0 % - 54.8%) with statistical significance (p = 0.018). This study suggests alpha lateralization which is an imbalance pattern between ipsilateral and contralateral is one of the main factors for improvement of performance. Accordingly, since the alpha liberalization before MI task could exert an effect on the MI phase, the analysis combined preparation with MI would derive highly benefit for the MI classification.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2502-2505
Number of pages4
ISBN (Electronic)9781728185262
DOIs
Publication statusPublished - 2020 Oct 11
Event2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 - Toronto, Canada
Duration: 2020 Oct 112020 Oct 14

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2020-October
ISSN (Print)1062-922X

Conference

Conference2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
Country/TerritoryCanada
CityToronto
Period20/10/1120/10/14

Bibliographical note

Funding Information:
* This research was supported in part by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No. 2017-0-00432, Development of non-invasive integrated BCI SW platform to control home appliances and external devices by user's thought via AR/VR interface), in part by Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science

Funding Information:
and ICT, MSIT) under Grant 2019R1A2C1003399, and in part by Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT, MSIT) under Grant NRF- 2020R1C1C1006773.

Publisher Copyright:
© 2020 IEEE.

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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