dc.citation.conferencePlace |
MY |
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dc.citation.conferencePlace |
Sutera Harbour ResortKota Kinabalu |
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dc.citation.title |
10th Asian Control Conference, ASCC 2015 |
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dc.contributor.author |
KiM, Min-Ki |
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dc.contributor.author |
Kim, Sung-Phil |
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dc.date.accessioned |
2023-12-19T22:36:09Z |
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dc.date.available |
2023-12-19T22:36:09Z |
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dc.date.created |
2016-03-11 |
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dc.date.issued |
2015-05-31 |
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dc.description.abstract |
This paper proposes a real-time method to eliminate eye-movement artifacts from frontal electroencephalography (EEG) signals using the total variation de-nosing algorithm. The proposed method is aimed to estimate electrooculography (EOG) artifacts from the EEG signals recorded from the frontal cortical areas using the total variation de-nosing algorithm. Then, it removes the estimated EOG artifacts in real time using a linear adaptive filter trained by the least-mean squares (LMS) algorithm. We demonstrate that our method can effectively remove the EOG artifact from the experimental EEG data. The proposed method may be used for various real-time applications such as non-invasive brain-computer interfaces. |
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dc.identifier.bibliographicCitation |
10th Asian Control Conference, ASCC 2015 |
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dc.identifier.doi |
10.1109/ASCC.2015.7244668 |
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dc.identifier.scopusid |
2-s2.0-84957641298 |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/35533 |
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dc.identifier.url |
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7244668 |
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dc.language |
한국어 |
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dc.publisher |
10th Asian Control Conference, ASCC 2015 |
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dc.title |
Artifact removal from EEG signals using the total variation method |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2015-05-31 |
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