Exploring the Number of Repetitions in Trials for the Performance Convergence of Classification in Motor Imagery Task with Hand-Grasping

Young Tak Kim, Seung Bo Lee, Hakseung Kim, Ji Hoon Jeong, Seong Whan Lee, Dong-Joo Kim

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

1 Citation (Scopus)

Abstract

Motor imagery-based brain-computer interface (BCI) has been widely used to translate user's motor intentions in BCI applications. In general, experiment trial of motor imagery task is repeated to improve the accuracy of the motor imagery-based BCI application, but it is not well known whether the accuracy would converge from a certain number of trial repetition. This study identified that how many trials are required in the classification model for motor imagery task with hand-grasping to show reliable classification performance. Five participants equipped with an electroencephalography device were enrolled, and they were requested to perform the motor imagery tasks with hand-grasping and unfolding. Trials were classified into hand-grasping, unfolding and resting. We observed that the classification performance is converged when more than 40 trials are used in the model. This finding could be utilized to develop reliable motor imagery-based BCI application with increasing the efficiency of the experiment.

Original languageEnglish
Title of host publication7th International Winter Conference on Brain-Computer Interface, BCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538681169
DOIs
Publication statusPublished - 2019 Feb 1
Event7th International Winter Conference on Brain-Computer Interface, BCI 2019 - Gangwon, Korea, Republic of
Duration: 2019 Feb 182019 Feb 20

Publication series

Name7th International Winter Conference on Brain-Computer Interface, BCI 2019

Conference

Conference7th International Winter Conference on Brain-Computer Interface, BCI 2019
CountryKorea, Republic of
CityGangwon
Period19/2/1819/2/20

Keywords

  • brain computer interface
  • hand-grasping
  • motor imagery task
  • performance convergence

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing
  • Neuroscience (miscellaneous)

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    Kim, Y. T., Lee, S. B., Kim, H., Jeong, J. H., Lee, S. W., & Kim, D-J. (2019). Exploring the Number of Repetitions in Trials for the Performance Convergence of Classification in Motor Imagery Task with Hand-Grasping. In 7th International Winter Conference on Brain-Computer Interface, BCI 2019 [8737308] (7th International Winter Conference on Brain-Computer Interface, BCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2019.8737308