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Tytuł pozycji:

Removal of Artifacts in Electroencephalogram Using Adaptive Infomax Algorithm of Blind Source Separation.

Tytuł:
Removal of Artifacts in Electroencephalogram Using Adaptive Infomax Algorithm of Blind Source Separation.
Autorzy:
Guo, Wanyou
Huang, Liyu
Gao, Li
Zhu, Tianqiao
Huang, Yuangui
Źródło:
Advanced Intelligent Computing Theories & Applications. With Aspects of Artificial Intelligence (9783540859833); 2008, p717-726, 10p
Książka
Infomax algorithm is one of the main strategies in blind source separation. The principle and improvement of the algorithm are introduced firstly in this paper. Nineteen-channel Electroencephalograms (EEGs) which include electromyogram, eye-movement and some other artifacts were decomposed by using this algorithm. Afterwards, three kinds of nonlinear parameters were calculated for all the independent components, and artifact components can be identified automatically by threshold settings. Finally, putting all the artifact components into zero, and projecting the other components to the scalp electrodes, then the purer Electroencephalograms can be gained. The study shows that the various artifacts can be separated from the EEGs successfully with the use of adaptive Infomax algorithm and removal of artifacts can be realized by signal reconstruction. Adaptive Infomax algorithm is a potential tool in removal of artifacts in physiological signal. [ABSTRACT FROM AUTHOR]
Copyright of Advanced Intelligent Computing Theories & Applications. With Aspects of Artificial Intelligence (9783540859833) is the property of Springer Nature / Books and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. 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.)

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