An EEG-based brain-computer interface for dual task driving detection

Yu Kai Wang, Shi An Chen, Chin-Teng Lin*

*Corresponding author for this work

Research output: Contribution to journalArticle

29 Scopus citations

Abstract

The development of brain-computer interfaces (BCI) for multiple applications has undergone extensive growth in recent years. Since distracted driving is a significant cause of traffic accidents, this study proposes one BCI system based on EEG for distracted driving. The removal of artifacts and the selection of useful brain sources are the essential and critical steps in the application of electroencephalography (EEG)-based BCI. In the first model, artifacts are removed, and useful brain sources are selected based on the independent component analysis (ICA). In the second model, all distracted and concentrated EEG epochs are recognized with a self-organizing map (SOM). This BCI system automatically identified independent components with artifacts for removal and detected distracted driving through the specific brain sources which are also selected automatically. The accuracy of the proposed system approached approximately 90% for the recognition of EEG epochs of distracted and concentrated driving according to the selected frontal and left motor components. (C) 2013 Published by Elsevier B.V.
Original languageEnglish
Pages (from-to) 85-93
Number of pages9
JournalNeurocomputing
Volume129
Issue numberSI
DOIs
StatePublished - 10 Apr 2014

Keywords

  • INDEPENDENT COMPONENT ANALYSIS; PREFRONTAL CORTEX; ELECTROENCEPHALOGRAM; RECOGNITION; ARTIFACTS; ALGORITHM; ATTENTION; REMOVAL; MEMORY

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