English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI

Lee, M.-H., Fazli, S., Mehnert, J., & Lee, S.-W. (2015). Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI. Pattern Recognition, 48(8), 2725-2737. doi:10.1016/j.patcog.2015.03.010.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0026-A3F0-B Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7C10-0
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Lee, Min-Ho1, Author
Fazli, Siamac1, Author
Mehnert, Jan2, Author              
Lee, Seong-Whan1, Author
Affiliations:
1Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea, ou_persistent22              
2TU Berlin, Germany, ou_persistent22              

Content

show
hide
Free keywords: Hybrid brain–computer interfacing; Combined EEG–NIRS; Classifier combination; Subject-dependent classification
 Abstract: Abstract Brain–computer interfaces (BCIs) allow users to control external devices by their intentions. Currently, most BCI systems are synchronous. They rely on cues or tasks to which a subject has to react. In order to design an asynchronous BCI one needs to be able to robustly detect an idle class. In this study, we examine whether multi-modal neuroimaging, based on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements, can assist in the robust detection of the idle class within a sensory motor rhythm-based BCI paradigm. We propose two types of subject-dependent classification strategies to combine the information of both modalities. Our results demonstrate that not only idle-state decoding can be significantly improved by exploiting the complementary information of multi-modal recordings, but also it is possible to minimize the delay of the system, caused by the slow inherent hemodynamic response of the NIRS signal.

Details

show
hide
Language(s): eng - English
 Dates: 2014-12-302014-05-232015-03-082015-03-182015-08
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.patcog.2015.03.010
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Pattern Recognition
  Other : Pattern Recognit.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 48 (8) Sequence Number: - Start / End Page: 2725 - 2737 Identifier: ISSN: 0031-3203
CoNE: https://pure.mpg.de/cone/journals/resource/954925431363