Mapping information flow of independent source to predict conscious level: A granger causality based brain-computer interface

Chun Hsiang Chuang*, Chih Sheng Huang, Chin Teng Lin, Li-Wei Ko, Jyh Yeong Chang, Jinn Min Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Recent studies have shown that the various brain networks over different cognitive states. In contrast to measure a physiological change over a single region, the information flows between brain regions described by effective connectivity provides an informative dynamic over the whole brain. In this study, we proposed a source information flow network based on the combination of Granger causality and support vector regression to predict driver's conscious level. This work provides the first application of using brain network to develop a brain-computer interface and obtain a sound result of performance.

Original languageEnglish
Title of host publicationProceedings - 2012 International Symposium on Computer, Consumer and Control, IS3C 2012
Pages813-816
Number of pages4
DOIs
StatePublished - 30 Jul 2012
Event2012 International Symposium on Computer, Consumer and Control, IS3C 2012 - Taichung, Taiwan
Duration: 4 Jun 20126 Jun 2012

Publication series

NameProceedings - 2012 International Symposium on Computer, Consumer and Control, IS3C 2012

Conference

Conference2012 International Symposium on Computer, Consumer and Control, IS3C 2012
CountryTaiwan
CityTaichung
Period4/06/126/06/12

Keywords

  • brain-computer interface
  • Granger causality
  • support vector regression
  • traffic safty

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