An EEG-Based Brain-Computer Interface for Dual Task Driving Detection

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

*Corresponding author for this work

研究成果: Conference contribution同行評審

6 引文 斯高帕斯(Scopus)

摘要

A novel detective model for driver distraction was proposed in this study. Driver distraction is a significant cause of traffic accidents during these years. To study human cognition under a specific driving task, one virtual reality (VR)-based simulation was built. Unexpected car deviations and mathematics questions with stimulus onset asynchrony (SOA) were designed. Electroencephalography (EEG) is a good index for the distraction level to monitor the effects of the dual tasks. Power changing in Frontal and Motor cortex were extracted for the detective model by independent component analysis (ICA). All distracting and non-distracting EEG epochs could be revealed the existence by self-organizing map (SOM). The results presented that this system approached about 90% accuracy to recognize the EEG epochs of non-distracting driving, and might be practicable for daily life.
原文English
主出版物標題NEURAL INFORMATION PROCESSING, PT I
發行者Springer-Verlag Berlin Heidelberg
頁面701-+
7062
ISBN(列印)978-3-642-24954-9 , 978-3-642-24955-6
DOIs
出版狀態Published - 十一月 2011

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