Classifying directions in continuous arm movement from EEG signals

Jeong Seok Woo, Klaus Muller, Seong Whan Lee

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

10 Citations (Scopus)

Abstract

EEG based upper limb rehabilitation has limitation on the control commands of neuro-prosthetics cannot deal with human's real movements. To resolve this problem, it is important to know about neural correlation of the directions of arm movement. Previous studies classified the directions of arm movement, using center-out task, only including y-z-axis movement. In this research, 4 subjects participated in experiment and the movement of their right arm in infinity shape (∞) divided into six part of symbol. Moreover, we used Common Spatial Pattern (CSP) algorithm to extract finer feature of EEG signal and Linear Discriminant Analysis (LDA) method to classify directions of movement. The result states that, average of classification accuracy was 74% and standard derivation was 0.08. In the topographical map at the center of infinity shape, we could observe the divided image of left and right side of the brain and FC3, F7 and C3 channels included most information about directions of movement. By the result of this study, we can confirm the possibility of controlling neuro-prosthetics and evidence of neurological basis of the arm movement.

Original languageEnglish
Title of host publication3rd International Winter Conference on Brain-Computer Interface, BCI 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479974948
DOIs
Publication statusPublished - 2015 Mar 30
Event2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 - Gangwon-Do, Korea, Republic of
Duration: 2015 Jan 122015 Jan 14

Other

Other2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015
CountryKorea, Republic of
CityGangwon-Do
Period15/1/1215/1/14

Fingerprint

Electroencephalography
Prosthetics
Arm
Discriminant analysis
Patient rehabilitation
Brain
Discriminant Analysis
Upper Extremity
Rehabilitation
Experiments
Direction compound
Research

Keywords

  • Arm movement direction
  • BCI
  • Common spatial pattern
  • EEG
  • Upper limb rehabilitation

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Cognitive Neuroscience
  • Sensory Systems

Cite this

Woo, J. S., Muller, K., & Lee, S. W. (2015). Classifying directions in continuous arm movement from EEG signals. In 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 [7073054] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2015.7073054

Classifying directions in continuous arm movement from EEG signals. / Woo, Jeong Seok; Muller, Klaus; Lee, Seong Whan.

3rd International Winter Conference on Brain-Computer Interface, BCI 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7073054.

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

Woo, JS, Muller, K & Lee, SW 2015, Classifying directions in continuous arm movement from EEG signals. in 3rd International Winter Conference on Brain-Computer Interface, BCI 2015., 7073054, Institute of Electrical and Electronics Engineers Inc., 2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015, Gangwon-Do, Korea, Republic of, 15/1/12. https://doi.org/10.1109/IWW-BCI.2015.7073054
Woo JS, Muller K, Lee SW. Classifying directions in continuous arm movement from EEG signals. In 3rd International Winter Conference on Brain-Computer Interface, BCI 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7073054 https://doi.org/10.1109/IWW-BCI.2015.7073054
Woo, Jeong Seok ; Muller, Klaus ; Lee, Seong Whan. / Classifying directions in continuous arm movement from EEG signals. 3rd International Winter Conference on Brain-Computer Interface, BCI 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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