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Real-time vigilance estimation using mobile wireless mindo EEG device with spring-loaded sensors
Conference paper   Peer reviewed

Real-time vigilance estimation using mobile wireless mindo EEG device with spring-loaded sensors

Li-Wei Ko, Chun-Hsiang Chuang, Chih-Sheng Huang, Yen-Hsuan Chen, Shao-Wei Lu, Lun-De Liao, Wan-Ting Chang and Chin-Teng Lin
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol.8027 LNAI, pp.450-458
2013

Abstract

Drowsy driving Humancomputer interface Mindo Wireless and dry EEG device Theoretical Computer Science Computer Science (all)
Monitoring the neurophysiological activities of human brain dynamics in an operational environment poses a severe measurement challenge using current laboratory-oriented biosensor technology. The goal of this research is to design, develop and test the wearable and wireless dry-electrode EEG human-computer interface (HCI) that can allow assessment of brain activities of participants actively performing ordinary tasks in natural body positions and situations within a real operational environment. Its implications in HCI were demonstrated through a sample application: vigilance-state prediction of participants performing a realistic sustained-attention driving task. Besides, this study further developed an online signal processing for extracting EEG features and assessing cognitive performance. We demonstrated the feasibility of using dry EEG sensors and miniaturized supporting hardware/software to continuously collect EEG data recorded from hairy sites (i.e., occipital region) in a realistic VR-based dynamic driving simulator. © 2013 Springer-Verlag Berlin Heidelberg.

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