RCPCH guideline appraisal on EEG after first seizure

C D Ferrie; J H Livingston; M A Clarke

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RCPCH guideline appraisal on EEG after first seizure

机译：首次癫痫发作后RCPCH对脑电图的评估

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A recent RCPCH guideline appraisal asserted: "There is no need for an EEG following a first simple afebrile seizure".1 This is puzzling. A "simple afebrile seizure" is not an entity recognised in the ILAE diagnostic scheme.2 More importantly, we disagree both with the recommendation and the contention that it is based on grade B evidence.

机译：RCPCH指南最近的评估断言：“第一次出现简单的高热惊厥后就不需要脑电图了。” 1这令人费解。 ILAE诊断方案不承认“简单的发热性癫痫发作”。2更重要的是，我们不同意该建议及其基于B级证据的观点。

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《Archives of disease in childhood. Education and practice edition》 |2004年第1期|共2页
作者
C D Ferrie; J H Livingston; M A Clarke;
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正文语种 eng
中图分类儿科学;
关键词
EEG; epilepsy; seizure;

机译：脑电图;癫痫;癫痫发作;

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1. RCPCH guideline appraisal on EEG after first seizure [J] . C D Ferrie, J H Livingston, M A Clarke Archives of disease in childhood. Education and practice edition . 2004,第1期

机译：首次癫痫发作后RCPCH对脑电图的评估
2. Systematic review of current guideline appraisals performed with the Appraisal of Guidelines for Research & Evaluation II instrument—a third of AGREE II users apply a cut-off for guideline quality [J] . Wiebke Hoffmann-E?er, Ulrich Siering, Edmund A.M. Neugebauer, Journal of Clinical Epidemiology . 2018,第期

机译：对当前指南评估的系统审查，并在研究方面的准则和AMP进行了评估; 评估II仪器 - 三分之一的II个人用户使用截止指南质量
3. The IPEG Pharmaco-EEG Guideline Committee: Guidelines for the Recording and Evaluation of Pharmaco-EEG Data in Man: The International Pharmaco-EEG Society (IPEG) (vol 66, pg 201, 2012) [J] . Jobert M., Wilson F. J., Ruigt G. S. F., Neuropsychobiology . 2018,第1期

机译：IPEG Pharmaco-EEG指南委员会：人类药房 - 欧宝数据的记录和评估准则：国际药物欧士署（IPEG）（IPEG）（第66号，PG 201，2012）
4. Epileptic seizure classification from intracranial EEG signals: A comparative study EEG-based seizure classification [C] . Md. Khayrul Bashar, Faruque Reza, Zamzuri Idris, 2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences . 2016

机译：颅内脑电图信号的癫痫性癫痫发作分类：基于脑电图的癫痫发作分类的比较研究
5. Multi-Feature Analysis of Eeg Signal on Seizure Patterns and Deep Neural Structures for Prediction of Epileptic Seizures [D] . Ma, Xinyuan. 2020

机译：癫痫发作模式和深神经结构对癫痫癫痫发作预测的多种特征分析
6. RCPCH guideline appraisal on EEG after first seizure [O] . C Ferrie, J Livingston, M Clarke 2004

机译：首次发作后RCPCH对脑电图的指南评估
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）

RCPCH guideline appraisal on EEG after first seizure

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