Nonlinear EEG Analysis In Epilepsy.

机译：癫痫的非线性脑电图分析。

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This overview presents potential applications of nonlinear time series analysis using EEGs derived from epilepsy patients. Apart from diagnostically oriented topics including localization of epileptic foci in different anatomical locations during the seizure-free interval I discuss possibilities for seizure anticipation which is one of the most challenging aspects of epileptology.

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Lehnertz, K.;
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年度 2001
页码 1-5
总页数 5
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Nonlinear analysis; Electroencephalography; Predictions; Time series analysis; Germany; Epilepsy; Foreign reports;

机译：非线性分析;脑电图;预测;时间序列分析;德国;癫痫;外国报道;

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1. Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy. [J] . Vulliemoz S, Rodionov R, Carmichael D NeuroImage . 2010,第4期

机译：连续的EEG源成像可增强对局灶性癫痫的EEG-fMRI分析。
2. Interictal spike analysis of high-density EEG in patients with partial epilepsy. [J] . Wang G, Worrell G, Yang L, Clinical neurophysiology . 2011,第6期

机译：部分性癫痫患者高密度脑电的壁间穗分析。
3. Analysis of background EEG activity in patients with juvenile myoclonic epilepsy. [J] . Santiago-Rodriguez E, Harmony T, Cardenas-Morales L, Seizure: the journal of the British Epilepsy Association . 2008,第5期

机译：青少年肌阵挛性癫痫患者的背景脑电活动分析。
4. AN EEG BASED NONLINEARITY ANALYSIS METHOD FOR SCHIZOPHRENIA DIAGNOSIS [C] . Qinglin Zhao, Bin Hu, Li Liu, Biomedical engineering . 2012

机译：基于脑电图的精神分裂症非线性诊断方法
5. EEG analysis of brain dynamical behavior with applications in epilepsy. [D] . Chien, Jui-Hong. 2011

机译：脑电行为的脑电图分析及其在癫痫中的应用。
6. Nonlinear analysis of EEG complexity in episode and remission phase of recurrent depression [O] . Milena Čukić, Miodrag Stokić, Slavoljub Radenković, 2020

机译：复发性抑郁症发作期和缓解期脑电图复杂性的非线性分析
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）

Nonlinear EEG Analysis In Epilepsy.

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