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| Presentation | 2011-06-24 11:10 Brain-computer interface based on steady-state visually evoked potentials -- Fundamental study on classification of attended stimulus based on amplitude change -- Daisuke Izuoka, Teruyoshi Sasayama, Hirokazu Kawaguchi, Tetsuo Kobayashi (Kyoto Univ)  NC2011-10 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In BCI with EEGs, it is important to extract features precisely using signal processing techniques. In this study, we focused on a BCI based on SSVEPs (steady-state visually evoked potentials) and investigated the method to analyze SSVEPs and examined classification accuracy when subjects focused on one of two visual stimuli flickering at different frequencies. Most of previous studies performed on this kind of BCI assume that subjects continued to attend on stimuli and do not consider the effects on attention by fatigue. Here, we performed the feature extraction in the short time period. After applied band pass filter tuned at narrowband stimulus frequency for measured EEGs, we separated signals and noises by using principal component analysis and independent component analysis. Subsequently, we extracted features by applying common spatial pattern obtained to amplitude in each short analysis period of the ingredient corresponding to signals. Finally, the attended stimulus was determined by classifying the features with support vector machine. A classification accuracy rate in all subjects was about 70%. This demonstrates the feasibility of the proposal method as a BCI. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | BCI / EEG / SSVEP / PCA / ICA / SVM / / | |
| Reference Info. | IEICE Tech. Rep., vol. 111, no. 96, NC2011-10, pp. 91-96, June 2011. | |
| Paper # | NC2011-10 | |
| Date of Issue | 2011-06-16 (NC) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NC2011-10 |
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| Conference Information | |
| Committee | NC IPSJ-BIO |
| Conference Date | 2011-06-23 - 2011-06-24 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | 50th Anniversary Memorial Hall, University of the Ryukyus |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Machine Learning Approach to Biodata Mining, and General |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2011-06-NC-BIO |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Brain-computer interface based on steady-state visually evoked potentials |
| Sub Title (in English) | Fundamental study on classification of attended stimulus based on amplitude change |
| Keyword(1) | BCI |
| Keyword(2) | EEG |
| Keyword(3) | SSVEP |
| Keyword(4) | PCA |
| Keyword(5) | ICA |
| Keyword(6) | SVM |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Daisuke Izuoka |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ) |
| 2nd Author's Name | Teruyoshi Sasayama |
| 2nd Author's Affiliation | Kyoto University (Kyoto Univ) |
| 3rd Author's Name | Hirokazu Kawaguchi |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ) |
| 4th Author's Name | Tetsuo Kobayashi |
| 4th Author's Affiliation | Kyoto University (Kyoto Univ) |
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| Speaker | Author-1 |
| Date Time | 2011-06-24 11:10:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2011-10 |
| Volume (vol) | vol.111 |
| Number (no) | no.96 |
| Page | pp.91-96 |
| #Pages | 6 |
| Date of Issue | 2011-06-16 (NC) |
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