Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification
DC Field | Value | Language |
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dc.contributor.author | Kam, Tae-Eui | - |
dc.contributor.author | Suk, Heung-Il | - |
dc.contributor.author | Lee, Seong-Whan | - |
dc.date.accessioned | 2021-09-06T01:40:39Z | - |
dc.date.available | 2021-09-06T01:40:39Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2013-05-02 | - |
dc.identifier.issn | 0925-2312 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/103253 | - |
dc.description.abstract | Neuronal power attenuation or enhancement in specific frequency bands over the sensorimotor cortex, called Event-Related Desynchronization (ERD) or Event-Related Synchronization (ERS), respectively, is a major phenomenon in brain activities involved in imaginary movement of body parts. However, it is known that the nature of motor imagery-related electroencephalogram (EEG) signals is non-stationary and highly variable over time and frequency. In this paper, we propose a novel method of finding a discriminative time- and frequency-dependent spatial filter, which we call 'non-homogeneous filter.' We adaptively select bases of spatial filters over time and frequency. By taking both temporal and spectral features of EEGs in finding a spatial filter into account it is beneficial to be able to consider non-stationarity of EEG signals. In order to consider changes of ERD/ERS patterns over the time-frequency domain, we devise a spectrally and temporally weighted classification method via statistical analysis. Our experimental results on the BCI Competition IV dataset II-a and BCI Competition II dataset IV clearly presented the effectiveness of the proposed method outperforming other competing methods in the literature. (C) 2012 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | SINGLE-TRIAL EEG | - |
dc.subject | BRAIN-COMPUTER INTERFACES | - |
dc.subject | EVENT-RELATED DESYNCHRONIZATION | - |
dc.subject | SPACE-TIME-FREQUENCY | - |
dc.subject | VOLUNTARY MOVEMENT | - |
dc.subject | PATTERNS | - |
dc.subject | COMMUNICATION | - |
dc.subject | SELECTION | - |
dc.title | Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kam, Tae-Eui | - |
dc.contributor.affiliatedAuthor | Suk, Heung-Il | - |
dc.contributor.affiliatedAuthor | Lee, Seong-Whan | - |
dc.identifier.doi | 10.1016/j.neucom.2012.12.002 | - |
dc.identifier.scopusid | 2-s2.0-84875095765 | - |
dc.identifier.wosid | 000317378000007 | - |
dc.identifier.bibliographicCitation | NEUROCOMPUTING, v.108, pp.58 - 68 | - |
dc.relation.isPartOf | NEUROCOMPUTING | - |
dc.citation.title | NEUROCOMPUTING | - |
dc.citation.volume | 108 | - |
dc.citation.startPage | 58 | - |
dc.citation.endPage | 68 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | SINGLE-TRIAL EEG | - |
dc.subject.keywordPlus | BRAIN-COMPUTER INTERFACES | - |
dc.subject.keywordPlus | EVENT-RELATED DESYNCHRONIZATION | - |
dc.subject.keywordPlus | SPACE-TIME-FREQUENCY | - |
dc.subject.keywordPlus | VOLUNTARY MOVEMENT | - |
dc.subject.keywordPlus | PATTERNS | - |
dc.subject.keywordPlus | COMMUNICATION | - |
dc.subject.keywordPlus | SELECTION | - |
dc.subject.keywordAuthor | Brain-Computer Interface (BCI) | - |
dc.subject.keywordAuthor | Electroencephalogram (EEG) | - |
dc.subject.keywordAuthor | Motor imagery classification | - |
dc.subject.keywordAuthor | Spatial filter optimization | - |
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