Motor imagery classification by means of source analysis methods

L. Qin; J. Deng; L. Ding; B. He

Motor imagery classification by means of source analysis methods

L. Qin
, J. Deng
, L. Ding
, B. He

Biomedical Engineering

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

We report our investigation of classification of imagined left and right hand movements by applying source analysis methods. Independent component analysis (ICA) is used as a spatio-temporal filter, then equivalent dipole analysis and cortical current density imaging methods are applied to reconstruct equivalent sources, to aid classification of motor imagery tasks in a human subject. The classification was considered correct if the equivalent source was found over the motor cortex in the corresponding hemisphere. A classification rate of about 80% was achieved in the human subject studied using both the equivalent dipole analysis and the cortical, current density imaging analysis.

Original language	English (US)
Pages (from-to)	4356-4358
Number of pages	3
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	26 VI
State	Published - 2004
Event	Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States Duration: Sep 1 2004 → Sep 5 2004

Keywords

Brain Computer Interface
EEG
Independent component analysis
Inverse Solution
Source Analysis

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title = "Motor imagery classification by means of source analysis methods",

abstract = "We report our investigation of classification of imagined left and right hand movements by applying source analysis methods. Independent component analysis (ICA) is used as a spatio-temporal filter, then equivalent dipole analysis and cortical current density imaging methods are applied to reconstruct equivalent sources, to aid classification of motor imagery tasks in a human subject. The classification was considered correct if the equivalent source was found over the motor cortex in the corresponding hemisphere. A classification rate of about 80\% was achieved in the human subject studied using both the equivalent dipole analysis and the cortical, current density imaging analysis.",

keywords = "Brain Computer Interface, EEG, Independent component analysis, Inverse Solution, Source Analysis",

author = "L. Qin and J. Deng and L. Ding and B. He",

year = "2004",

language = "English (US)",

volume = "26 VI",

pages = "4356--4358",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 ; Conference date: 01-09-2004 Through 05-09-2004",

}

TY - JOUR

T1 - Motor imagery classification by means of source analysis methods

AU - Qin, L.

AU - Deng, J.

AU - Ding, L.

AU - He, B.

PY - 2004

Y1 - 2004

N2 - We report our investigation of classification of imagined left and right hand movements by applying source analysis methods. Independent component analysis (ICA) is used as a spatio-temporal filter, then equivalent dipole analysis and cortical current density imaging methods are applied to reconstruct equivalent sources, to aid classification of motor imagery tasks in a human subject. The classification was considered correct if the equivalent source was found over the motor cortex in the corresponding hemisphere. A classification rate of about 80% was achieved in the human subject studied using both the equivalent dipole analysis and the cortical, current density imaging analysis.

AB - We report our investigation of classification of imagined left and right hand movements by applying source analysis methods. Independent component analysis (ICA) is used as a spatio-temporal filter, then equivalent dipole analysis and cortical current density imaging methods are applied to reconstruct equivalent sources, to aid classification of motor imagery tasks in a human subject. The classification was considered correct if the equivalent source was found over the motor cortex in the corresponding hemisphere. A classification rate of about 80% was achieved in the human subject studied using both the equivalent dipole analysis and the cortical, current density imaging analysis.

KW - Brain Computer Interface

KW - EEG

KW - Independent component analysis

KW - Inverse Solution

KW - Source Analysis

UR - https://www.scopus.com/pages/publications/11144278557

UR - https://www.scopus.com/pages/publications/11144278557#tab=citedBy

M3 - Conference article

AN - SCOPUS:11144278557

SN - 0589-1019

VL - 26 VI

SP - 4356

EP - 4358

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004

Y2 - 1 September 2004 through 5 September 2004

ER -

Motor imagery classification by means of source analysis methods

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