Volume 8 Number 9 ( Sep. 2013)
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JSW 2013 Vol.8(9): 2385-2390 ISSN: 1796-217X
doi: 10.4304/jsw.8.9.2385-2390

An Exponential Power Ratio Index based Algorithm for Analysis of Alcoholic EEG Signal

Mingyue Yan
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China

Abstract—This paper presents a new Algorithm to analyze the Electroencephalography (EEG) signal, which is regarded as an important way to analyze the alcoholism. In order to distinguish the nonlinear characteristics of EEG with alcoholic people and the control, an exponential power ratio index (EPRI) is proposed to quantify the slow wave and fast wave power features of the EEG signal, and the Independent Component Analysis (ICA) and Support Vector Machine (SVM) are combined for analysis. The proposed method is implemented on the real data sets acquired from UCI common databases, which have been studied by some research groups. The results suggest that the proposed method is valid for analysis of EEG signal in alcoholism.

Index Terms—Electroencephalography (EEG), Independent Component Analysis (ICA), Support Vector Machine (SVM), Time Series, Feature Analysis

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Cite: Mingyue Yan, "An Exponential Power Ratio Index based Algorithm for Analysis of Alcoholic EEG Signal," Journal of Software vol. 8, no. 9, pp. 2385-2390, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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