Detecting voluntary gait initiation/termination intention using EEG

Junhyuk Choi, Song Joo Lee, Seung-Jong Kim, Jong Min Lee, Hyungmin Kim

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

1 Citation (Scopus)

Abstract

In this study, we employed a linear classifier to grasp the abstract features of electroencephalography (EEG) for recognizing voluntary gait intention and termination. We monitored Mu-band EEG to find gait intention and tried to detect a movement on/offset. Considerable gait-related (de) synchronization occurred hence, amplified by common spatial pattern (CSP). Performance of the classifier was evaluated in terms of classification success rates and false positive rates.

Original languageEnglish
Title of host publication2018 6th International Conference on Brain-Computer Interface, BCI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-3
Number of pages3
ISBN (Electronic)9781538625743
DOIs
Publication statusPublished - 2018 Mar 9
Externally publishedYes
Event6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of
Duration: 2018 Jan 152018 Jan 17

Publication series

Name2018 6th International Conference on Brain-Computer Interface, BCI 2018
Volume2018-January

Other

Other6th International Conference on Brain-Computer Interface, BCI 2018
CountryKorea, Republic of
CityGangWon
Period18/1/1518/1/17

Keywords

  • ASR
  • CSP
  • EEG
  • gait intention
  • LDA

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Behavioral Neuroscience

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  • Cite this

    Choi, J., Lee, S. J., Kim, S-J., Lee, J. M., & Kim, H. (2018). Detecting voluntary gait initiation/termination intention using EEG. In 2018 6th International Conference on Brain-Computer Interface, BCI 2018 (pp. 1-3). (2018 6th International Conference on Brain-Computer Interface, BCI 2018; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2018.8311532