DocumentCode
2378778
Title
Electroencephalograph (EEG) signal processing method of motor imaginary potential for attention level classification
Author
Ming, Dong ; Xi, Youyuan ; Zhang, Mingming ; Qi, Hongzhi ; Cheng, Longlong ; Wan, Baikun ; Li, Liyong
Author_Institution
Dept. of Biomed. Eng., Tianjin Univ., Tianjin, China
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
4347
Lastpage
4351
Abstract
Research of visual attention is one of the important domains of psychology and neurophysiology. In this study, an attention related electroencephalograph (EEG) signal processing method was proposed to distinguish the different levels of people´s attention during the imaginary limbs motor. There were two EEG feedback experiments (playing tennis and walking) to measure the different levels of visual attention. Three imaginary motor tasks (attention, inattention, and rest task) were performed with the flash stimulus displayed on the screen in the experiments. A nonlinear dynamics parameter of multi-scale entropy (MSE) was extracted from those EEG data recorded. According to the statistics analysis of 14 subjects, there was an obvious declining tendency of MSE with the level of attention declining, which validated the effectiveness of the proposed method to classify the visual attention level.
Keywords
electroencephalography; entropy; medical signal processing; psychology; vision; attention level classification; electroencephalograph signal processing; imaginary limbs motor; motor imaginary potential; multiscale entropy; neurophysiology; playing tennis; psychology; visual attention; walking; Adult; Algorithms; Attention; Brain; Brain Mapping; Central Nervous System; Electroencephalography; Feedback; Humans; Models, Statistical; Motor Neurons; Nonlinear Dynamics; Signal Processing, Computer-Assisted; Time Factors; Walking;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5332743
Filename
5332743
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