Research on the methods for electroencephalogram feature extraction based on blind source separation / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1195-1201, 2014.
Article
in Chinese
| WPRIM
| ID: wpr-234431
ABSTRACT
In the present investigation, we studied four methods of blind source separation/independent component analysis (BSS/ICA), AMUSE, SOBI, JADE, and FastICA. We did the feature extraction of electroencephalogram (EEG) signals of brain computer interface (BCI) for classifying spontaneous mental activities, which contained four mental tasks including imagination of left hand, right hand, foot and tongue movement. Different methods of extract physiological components were studied and achieved good performance. Then, three combined methods of SOBI and FastICA for extraction of EEG features of motor imagery were proposed. The results showed that combining of SOBI and ICA could not only reduce various artifacts and noise but also localize useful source and improve accuracy of BCI. It would improve further study of physiological mechanisms of motor imagery.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Physiology
/
Tongue
/
Algorithms
/
Signal Processing, Computer-Assisted
/
Brain
/
Artifacts
/
Electroencephalography
/
Brain-Computer Interfaces
/
Foot
/
Hand
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2014
Type:
Article
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