International Journal of Technology Enhanced Learning (IJTEL)

Ambjoern Naeve

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International Journal of Technology Enhanced Learning (IJTEL)

机译：国际技术增强学习杂志（IJTEL）

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IJTEL fosters multidisciplinary discussion and research on technology enhanced learning (TEL) approaches at the individual, organisational, national and global levels. Its key objective is to be the leading scholarly scientific journal for all those interested in, researching and contributing to the technology enhanced learning episteme.

机译：IJTEL促进在个人，组织，国家和全球各级进行技术增强学习（TEL）方法的多学科讨论和研究。它的主要目标是成为所有对研究，研究和促进技术增强的学习认识有贡献的学者的领先学术期刊。

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《International Journal of Learning and Change》 |2012年第4期|233-233|共1页
作者
Ambjoern Naeve;
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1. International Journal of Technology Enhanced Learning (IJTEL) [J] . International Journal of Learning and Change . 2011,第2期

机译：国际技术增强学习杂志（IJTEL）
2. International Journal of Technology Enhanced Learning (IJTEL) [J] . International journal of risk assessment and management . 2009,第3a4期

机译：国际技术增强学习杂志（IJTEL）
3. International Journal of Technology Assessment in Health Care Official journal of Health Technology Assessment International (HTAi) [J] . Makela Marjukka Infection control and hospital epidemiology . 2016,第2期

机译：国际卫生保健技术评估杂志国际卫生技术评估国际杂志（HTAi）
4. The usage of learning journals in a Technology Management Education [C] . Charlotta, Fredrik, Erlingsdottir Gudbjorg, First International Technology Management Conference . 2011

机译：学习期刊在技术管理教育中的使用
5. A journal study of the spoken English learning experience of prospective international teaching assistants. [D] . Capraro, Fernanda Patricia. 2002

机译：一份针对未来国际助教的英语口语学习经历的期刊研究。
6. Editorial: Digital Skills and Life-Long Learning: Digital Learning as a New Insight of Enhanced Learning by the Innovative Approach Joining Technology and Cognition [O] . Dina Di Giacomo, Pierpaolo Vittorini, Pilar Lacasa -1

机译：社论：数字技能与终身学习：将技术与认知相结合的创新方法将数字学习作为增强学习的新视角
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）

International Journal of Technology Enhanced Learning (IJTEL)

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