Classification of the Direction Perceived EEG based on ICA-F-score Approach

机译：基于ICA-F得分法的方向感知脑电分类

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An experiment was designed to record the electroencephalography, when people caught the vision of different directional moving. Independent components analysis was used to analyze the EEG signal. The selection of independent component has received a great deal of attention in the field of signal processing and image processing. Here, F-score of multisets was used to select the valuable independent components. The analysis result showed that separable features could be obtained when people had different directional perception.

机译：当人们捕捉到不同方向运动的视觉时，设计了一个记录脑电图的实验。使用独立成分分析来分析脑电信号。在信号处理和图像处理领域中，独立分量的选择引起了广泛的关注。在这里，多集的F得分用于选择有价值的独立组件。分析结果表明，当人们具有不同的方向感时，可以获得可分离的特征。

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《The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议）论文集》|2008年|1884-1887|共4页
会议地点 Shanghai(CN)
作者
Jing Jin; Xingyu Wang; Jianhua Zhang;
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作者单位

School of Information Science and Engineering East China University of Science and Technology Shanghai 200237, China P.R;

School of Information Science and Engineering East China University of Science and Technology Shanghai 200237, China P.R;

School of Information Science and Engineering East China University of Science and Technology Shanghai 200237, China P.R;

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会议组织
原文格式 PDF
正文语种 eng
中图分类信息处理技术;
关键词
EEG; ICA; F-score; Selection;

机译：是;伊卡，得分后；选拔;

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7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

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Classification of the Direction Perceived EEG based on ICA-F-score Approach

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