Title: A Real-Time Wireless Brain-Computer Interface System for Drowsiness Detection
Authors: Lin, Chin-Teng
Chang, Che-Jui
Lin, Bor-Shyh
Hung, Shao-Hang
Chao, Chih-Feng
Wang, I-Jan
影像與生醫光電研究所
資訊工程學系
電機工程學系
腦科學研究中心
Institute of Imaging and Biomedical Photonics
Department of Computer Science
Department of Electrical and Computer Engineering
Brain Research Center
Keywords: Drowsiness detection;electroencephalogram (EEG);brain-computer interface (BCI)
Issue Date: 1-Aug-2010
Abstract: A real-time wireless electroencephalogram (EEG)-based brain-computer interface (BCI) system for drowsiness detection has been proposed. Drowsy driving has been implicated as a causal factor in many accidents. Therefore, real-time drowsiness monitoring can prevent traffic accidents effectively. However, current BCI systems are usually large and have to transmit an EEG signal to a back-end personal computer to process the EEG signal. In this study, a novel BCI system was developed to monitor the human cognitive state and provide biofeedback to the driver when drowsy state occurs. The proposed system consists of a wireless physiological signal-acquisition module and an embedded signal-processing module. Here, the physiological signal-acquisition module and embedded signal-processing module were designed for long-term EEG monitoring and real-time drowsiness detection, respectively. The advantages of low ower consumption and small volume of the proposed system are suitable for car applications. Moreover, a real-time drowsiness detection algorithm was also developed and implemented in this system. The experiment results demonstrated the feasibility of our proposed BCI system in a practical driving application.
URI: http://dx.doi.org/10.1109/TBCAS.2010.2046415
http://hdl.handle.net/11536/32357
ISSN: 1932-4545
DOI: 10.1109/TBCAS.2010.2046415
Journal: IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
Volume: 4
Issue: 4
Begin Page: 214
End Page: 222
Appears in Collections:Articles


Files in This Item:

  1. 000282947200002.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.