DocumentCode
2744441
Title
Motor imagery classification by means of source analysis methods
Author
Qin, L. ; Deng, J. ; Ding, L. ; He, B.
Author_Institution
Dept. of Biomed. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume
2
fYear
2004
fDate
1-5 Sept. 2004
Firstpage
4356
Lastpage
4358
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
band-pass filters; bioelectric phenomena; biomechanics; biomedical MRI; current density; electroencephalography; independent component analysis; medical signal processing; signal classification; spatiotemporal phenomena; cortical current density imaging; equivalent dipole analysis; equivalent source reconstruction; hand movements; independent component analysis; motor cortex; motor imagery classification; source analysis methods; spatio-temporal filter; Brain computer interfaces; Current density; Electrodes; Electroencephalography; Filters; Humans; Image analysis; Independent component analysis; Scalp; Testing; Brain Computer Interface; EEG; Independent component analysis; Inverse Solution; Source Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-8439-3
Type
conf
DOI
10.1109/IEMBS.2004.1404212
Filename
1404212
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