English  |  正體中文  |  简体中文  |  Items with full text/Total items : 26999/38800
Visitors : 2400236      Online Users : 73
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46485

Title: Real-time assessment of vigilance level using an innovative Mindo4 wireless EEG system
Authors: Chin-Teng Lin
Chun-Hsiang Chuang
Chih-Sheng Huang
Yen-Hsuan Chen
Li-Wei Ko
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Electroencephalography;Fatigue;Wireless communication;Vehicles;Spectral analysis;Wireless sensor networks;Forehead
Date: 2013-05
Issue Date: 2018-05-21T03:42:00Z
Publisher: Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Abstract: Abstract:
Monitoring the neurophysiological activities of driver in an operational environment poses a severe measurement challenge using a current laboratory-oriented biosensor technology. The aims of this research are to 1) introduce a dry and wireless EEG system used for conveniently recording EEG signals from forehead regions, 2) propose an effective system for processing EEG recordings and translating them into the vigilance level, and 3) implement the proposed system with a JAVA-based graphical user interface (GUI) for online analysis. To validate the performance of the proposed system, this study recruited eight voluntary subjects to participate a 90-min sustained-attention driving task in a virtual-realistic driving environment. Physiological evidence obtained from the power spectral analysis showed that the dry EEG system could distinguish an alert EEG from a drowsy EEG by evaluating the spectral dynamics of delta and alpha activities. Furthermore, the experimental result of the comparison of the prediction performance using four forehead electrode sites (AF8, FP2, FP1, and AF7) implied that a single-electrode EEG signal used in the mobile and wireless EEG system is able to obtain a high prediction accuracy (~93%). Taken together, the proposed system applied a dry-EEG device combined with an effective algorithm can be a promising technology for real driving applications.
Relation: pp.1528-1531
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46485
Appears in Collections:[資訊工程學系] 演講及研討會

Files in This Item:

File Description SizeFormat
index.html0KbHTML20View/Open


All items in NTOUR are protected by copyright, with all rights reserved.

 


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback