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Content Provider | IEEE Xplore Digital Library |
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Author | Yuanqing Li Jinyi Long Tianyou Yu Zhuliang Yu Chuanchu Wang Haihong Zhang Cuntai Guan |
Copyright Year | 2010 |
Description | Author affiliation: Institute for Infocomm Research, Singapore 119613 (Chuanchu Wang; Haihong Zhang; Cuntai Guan) || School of Automation Science and Engineering, South China University of Technology, 510640, China (Yuanqing Li; Jinyi Long; Tianyou Yu; Zhuliang Yu) |
Abstract | In this paper, a hybrid EEG-based brain computer interface (BCI) is designed for two-dimensional cursor control. In our approach, two brain activity patterns, i.e., motor imagery and P300 potential, are used for controlling the horizontal and the vertical movements of the cursor respectively. A real-time BCI system based on this approach is implemented and evaluated through an online experiment. Six subjects attending this experiment can perform 2-D cursor control effectively. Our experimental results show that the system has the following merits compared with prior systems: 1) it does not rely on intensive user training; 2) it allows cursor movement between arbitrary positions. |
Starting Page | 4205 |
Ending Page | 4208 |
File Size | 556935 |
Page Count | 4 |
File Format | |
ISBN | 9781424441235 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2010.5627394 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-08-31 |
Publisher Place | Argentina |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Electroencephalography Brain models Support vector machines Rhythm Feature extraction Training P300 potential Brain-computer interface (BCI) electroencephalogram (EEG) 2-D cursor control mu rhythm |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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