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Sensors 2013, 13(8), 10783-10801; doi:10.3390/s130810783
Article

Automatic and Direct Identification of Blink Components from Scalp EEG

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Received: 15 July 2013; in revised form: 8 August 2013 / Accepted: 12 August 2013 / Published: 16 August 2013
(This article belongs to the Special Issue Biomedical Sensors and Systems)
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Abstract: Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn’t need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects.
Keywords: scalp EEG; correlation; eye blink artifact; independent component analysis (ICA); identify scalp EEG; correlation; eye blink artifact; independent component analysis (ICA); identify
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Kong, W.; Zhou, Z.; Hu, S.; Zhang, J.; Babiloni, F.; Dai, G. Automatic and Direct Identification of Blink Components from Scalp EEG. Sensors 2013, 13, 10783-10801.

AMA Style

Kong W, Zhou Z, Hu S, Zhang J, Babiloni F, Dai G. Automatic and Direct Identification of Blink Components from Scalp EEG. Sensors. 2013; 13(8):10783-10801.

Chicago/Turabian Style

Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun. 2013. "Automatic and Direct Identification of Blink Components from Scalp EEG." Sensors 13, no. 8: 10783-10801.


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