LOCATION OF ELECTRODES FOR RECORDING THE EEG SIGNAL: SELECTED PROBLEMS

T. ZYSS; A. STANISLAWCZYK; B. SAWICKI

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LOCATION OF ELECTRODES FOR RECORDING THE EEG SIGNAL: SELECTED PROBLEMS

机译：记录脑电信号的电极位置：选定的问题

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The paper deals with problems connected with location of electrodes for recording the EEG signal in standard and enhanced system. A procedure of taking measurements on the head has been presented. The authors indicate the necessity of applying precise spatial coordinates of electrodes in scientific research.

机译：本文处理与在标准和增强系统中记录脑电信号的电极位置有关的问题。已经提出了在头部进行测量的程序。作者指出在科学研究中应用精确的电极空间坐标的必要性。

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《Journal of Technical Physics》 |2006年第4期|p.179-204|共26页
作者
T. ZYSS; A. STANISLAWCZYK; B. SAWICKI;
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作者单位

Department of Psychiatry Collegium Medicum Jagellonian University Kopernika 21, 31-501 Krakow, Poland;

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正文语种 eng
中图分类工程物理学;
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机译：面向新兴的脑电图应用：一种新颖的可打印柔性Ag / AgCl干电极阵列，可在前额部位稳健地记录脑电信号
2. Effects of various typical electrodes and electrode gels combinations on MRI signal-to-noise ratio and safety issues in EEG-fMRI recording [J] . Gao Dongrui, Li Mingzhe, Li Jianfu, Biocybernetics and biomedical engineering . 2016,第1期

机译：各种典型电极和电极凝胶组合对EEEG-fMRI记录中MRI信噪比和安全性问题的影响
3. An EEG (electroencephalogram) recording system with carbon wire electrodes for simultaneous EEG-fMRI (functional magnetic resonance imaging) recording. [J] . Negishi M, Abildgaard M, Laufer I, Journal of Neuroscience Methods . 2008,第1期

机译：具有碳线电极的EEG（脑电图）记录系统，用于同时进行EEG-fMRI（功能磁共振成像）记录。
4. An Emotional Face Evoked EEG Signal Recognition Method Based on Optimal EEG Feature and Electrodes Selection [C] . Lijuan Duan, Xuebin Wang, Zhen Yang, International conference on neural information processing;ICONIP 2011 . 2011

机译：基于最优脑电特征和电极选择的情感面诱发脑电信号识别方法
5. An active micromachined scalp electrode array for EEG signal recording. [D] . Alizadeh-Taheri, Babak. 1994

机译：用于脑电信号记录的有源微加工头皮电极阵列。
6. An EEG (electroencephalogram) recording system with carbon wire electrodes for simultaneous EEG-fMRI (functional magnetic resonance imaging) recording [O] . Michiro Negishi, Mark Abildgaard, Ilan Laufer, -1

机译：具有碳丝电极的EEG（脑电图）记录系统用于同时进行EEG-fMRI（功能磁共振成像）记录
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

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

LOCATION OF ELECTRODES FOR RECORDING THE EEG SIGNAL: SELECTED PROBLEMS

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