Design of a brain-controlled robot arm system based on upper-limb movement imagery

Ji Hoon Jeong, Keun Tae Kim, Yong Deok Yun, Seong Whan Lee

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

7 Citations (Scopus)

Abstract

This paper presents a prototype for a brain-controlled robot arm system using a variety of upper-limb movement imagery. To do that, we have designed the experimental environment based on brain signals. The experimental system architecture was modularized into three main components: BMI, network, and control parts. Six subjects participated in our experiments. The subject performed various upper-limb actual movement and imagery task. Each task consisted of three different movement/imagery: Arm reaching tasks, hand grasping tasks, and wrist twisting tasks. We confirmed the classification accuracies are 22.65%, 50.79%, and 54.44%, respectively. Moreover, we will demonstrate that brain-controlled robot arm system can achieve a high-level task in multi-dimensional space.

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
Volume2018-January
ISBN (Electronic)9781538625743
DOIs
Publication statusPublished - 2018 Mar 9
Event6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of
Duration: 2018 Jan 152018 Jan 17

Other

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

Keywords

  • a robot arm
  • brain machine interface
  • electro-encephalography
  • upper-limb movement imagery

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Behavioral Neuroscience

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  • Cite this

    Jeong, J. H., Kim, K. T., Yun, Y. D., & Lee, S. W. (2018). Design of a brain-controlled robot arm system based on upper-limb movement imagery. In 2018 6th International Conference on Brain-Computer Interface, BCI 2018 (Vol. 2018-January, pp. 1-3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2018.8311514