On the Calculation of the Morlet Wavelet Used for the Analysis of the Dynamics of Electroencephalogram Signal Responses

A. D. Mansfeld

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On the Calculation of the Morlet Wavelet Used for the Analysis of the Dynamics of Electroencephalogram Signal Responses

机译：用于脑电信号响应动力学分析的Morlet小波的计算

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The function describing the Morlet wavelet transform used for calculating spectrograms characterizing cerebrum brain electroencephalograms is analytically integrated. It is shown that the exact integration reduces the spurious signal level, a circumstance that facilitates obtaining ridges of wavelet spectrograms.

机译：描述性地集成了描述Morlet小波变换的功能，该功能用于计算表征大脑脑电图的频谱图。结果表明，精确的积分降低了杂散信号电平，这种情况有助于获得小波频谱图的脊。

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《Journal of Communications Technology and Electronics》 |2012年第4期|p.429-431|共3页
作者
A. D. Mansfeld;
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Kotel'nikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences,Mokhovayaul. 11, korp. 7, Moscow, 125009 Russia;

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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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On the Calculation of the Morlet Wavelet Used for the Analysis of the Dynamics of Electroencephalogram Signal Responses

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