An Epileptic Electroencephalogram Signal Classification Method Based on Variational Mode Decomposition

被引：0
|
作者：
Zhang X.-J. [1 ,2 ]
Jing P. [1 ]
He T. [1 ,2 ]
Sun Z.-X. [3 ,4 ]
机构：
[1] School of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing
[2] Nation-Local Joint Project Engineering Lab of RF Integration & Micropackage, Nanjing University of Posts and Telecommunications, Nanjing
[3] Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing
[4] Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2020年 / 48卷 / 12期
关键词：
Epileptic electroencephalogram; Refined composite multiscale dispersion entropy; Refined composite multiscale fuzzy entropy; Support vector machine; Variational mode decomposition;
D O I：
10.3969/j.issn.0372-2112.2020.12.024
中图分类号：
学科分类号：
摘要：
Epilepsy is a recurrent cerebral disease, and electroencephalogram (EEG) provides a non-invasive way to identify epileptogenic sites in the brain. In order to distinguish focal and non-focal epilepsy EEG signals, this paper proposes an automated epileptic EEG detection method based on variational mode decomposition. Firstly, the original signals are divided into several sub-signals, which are decomposed into intrinsic mode functions by using the variational mode decomposition (VMD). Furthermore, refined composite multiscale dispersion entropy (RCMDE) and refined composite multiscale fuzzy entropy (RCMFE) are extracted from each intrinsic mode function. Finally, the support vector machine (SVM) is used to classify characteristics. For an epilepsy EEG signals' public data set, the final experimental performance measures of accuracy, sensitivity, and specificity reach 94.24%, 95.58% and 90.64% respectively, and the area under the ROC curve is 0.978. © 2020, Chinese Institute of Electronics. All right reserved.
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页码：2469 / 2475
页数：6
相关论文
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