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Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification

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Title: Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification
Authors: Kam, Tae-Eui1 kamte@korea.ac.kr, Suk, Heung-Il1 hisuk@korea.ac.kr, Lee, Seong-Whan2 sw.lee@korea.ac.kr
Source: Neurocomputing. May2013, Vol. 108, p58-68. 11p.
Subjects: Electroencephalography, Beamforming, Mathematical optimization, Image processing, Evoked potentials (Electrophysiology), Neurons, Statistics
Abstract: 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. [Copyright &y& Elsevier]
Copyright of Neurocomputing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 86407994
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification
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  Data: <searchLink fieldCode="AR" term="%22Kam%2C+Tae-Eui%22">Kam, Tae-Eui</searchLink><relatesTo>1</relatesTo><i> kamte@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Suk%2C+Heung-Il%22">Suk, Heung-Il</searchLink><relatesTo>1</relatesTo><i> hisuk@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Seong-Whan%22">Lee, Seong-Whan</searchLink><relatesTo>2</relatesTo><i> sw.lee@korea.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Neurocomputing%22">Neurocomputing</searchLink>. May2013, Vol. 108, p58-68. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Beamforming%22">Beamforming</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Evoked+potentials+%28Electrophysiology%29%22">Evoked potentials (Electrophysiology)</searchLink><br /><searchLink fieldCode="DE" term="%22Neurons%22">Neurons</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink>
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  Label: Abstract
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  Data: 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. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Neurocomputing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.neucom.2012.12.002
    Languages:
      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 58
    Subjects:
      – SubjectFull: Electroencephalography
        Type: general
      – SubjectFull: Beamforming
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Image processing
        Type: general
      – SubjectFull: Evoked potentials (Electrophysiology)
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      – SubjectFull: Neurons
        Type: general
      – SubjectFull: Statistics
        Type: general
    Titles:
      – TitleFull: Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification
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            NameFull: Kam, Tae-Eui
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            NameFull: Suk, Heung-Il
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            NameFull: Lee, Seong-Whan
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            – D: 02
              M: 05
              Text: May2013
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              Y: 2013
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              Value: 108
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            – TitleFull: Neurocomputing
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