Application of EEG for multimodal human-machine interface

Jangwoo Park, Il Woo, Shinsuk Park

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

10 Citations (Scopus)


There are many input modalities for human-machine interface (HMI). Brain-signal that is one of biosignal has been studied as an input modality for HMI. Brain-signal based HMI can help disabled people to communicate with a machine using the brain's electrical activity. this study is focuses on usability of the EEG-based HMI's for available tools in real life and possibility of the EEG signal as input modality of multimodal interface. This study attempt to explore the electroencephalogram (EEG) signal measurement and analysis methods related to concentration for multimodal Interface. The experiments have been performed with various tasks, such as self-concentration, self-arithmetic (non-display), self-arithmetic (show display) and eye-closing. EEG signals are recorded while subjects perform each task on Fz, Cz, Pz. The receiver operating characteristic (ROC) curve analysis is to determine the threshold on each task. Rate of distinction range is 50.32% ∼ 56.77% with the threshold about self-arithmetic and 71.67%∼78.33% with the threshold about eye-closing. There are some meaningful results about threshold, self-arithmetic and eye-close activity. It can be used for brain-machine interface and multi-modal interface.

Original languageEnglish
Title of host publicationICCAS 2012 - 2012 12th International Conference on Control, Automation and Systems
Number of pages5
Publication statusPublished - 2012
Event2012 12th International Conference on Control, Automation and Systems, ICCAS 2012 - Jeju, Korea, Republic of
Duration: 2012 Oct 172012 Oct 21

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833


Other2012 12th International Conference on Control, Automation and Systems, ICCAS 2012
Country/TerritoryKorea, Republic of


  • Electroencephalogram(EEG)
  • Human-machine interface (HMI)
  • Mental arithmetic
  • Receiver operating characteristic (ROC)
  • Task difficulty

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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