Hybrid brain-computer interface based on EEG and NIRS modalities

Min Ho Lee, Siamac Fazli, Jan Mehnert, Seong Whan Lee

Research output: Contribution to conferencePaperpeer-review

14 Citations (Scopus)

Abstract

Non-invasive brain-computer interfaces (BCIs) allow users to control external devices by their intentions. Currently, most BCI systems are synchronous, which means, they rely on cues or tasks to which a subject has to react. It would be more useful for users if they could control a device at their own will (i.e., asynchronous BCIs). However, previous asynchronous BCI systems that rely on non-invasive electroencephalogram (EEG) measurements, are not accurate and stable enough for real world applications. Previously, hybrid BCI systems, relying on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements, have been shown to increase the classification performance of synchronous motor imagery (MI) tasks. In this study, we present a first report on an asynchronous multi-modal hybrid BCI, based on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements and propose novel subject-dependent classification strategies for combining both measurements.

Original languageEnglish
DOIs
Publication statusPublished - Jan 1 2014
Externally publishedYes
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: Feb 17 2014Feb 19 2014

Conference

Conference2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
CountryKorea, Republic of
CityGangwon
Period2/17/142/19/14

Keywords

  • Asynchronous BCI
  • Combined EEG-NIRS
  • Hybrid Brain-Computer Interface
  • Subject-dependent Classification

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Human Factors and Ergonomics

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