.png){kind=icon}
返回
Automatic epilepsy detection using wavelet-based nonlinear analysis and optimized SVM
.png){kind=icon}
PRE
AI
DOI：10.1016/j.bbe.2016.07.004.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Aiming at the problems of low accuracy, poor universality and functional singleness for seizure detection, an effective approach using wavelet-based non-linear analysis and genetic algorithm optimized support vector machine (GA-SVM) is proposed to deal with five challenging classification problems in this study. Instead of the traditional discrete wavelet transform (DWT), we attempt to explore the ability of double-density discrete wavelet transform (DD-DWT) to decompose the original EEG into specific sub-bands. The Hurst exponent (HE) and fuzzy entropy (FuzzyEn) are extracted as input features and then fed into two classifiers. On using these ranking non-linear features, the GA-SVM configured with fewer features is found to achieve the prominent classification performance for various combinations such as AB-CD-E, A-D-E, ABCD-E, C-E and D-E, achieving accuracies of 99.36%, 99.60%, 99.40%, 100% and 100%, respectively. The results have indicated that our scheme is not only appropriate in solving problems with multiple classes but also of lower complexity and better expansibility. These characteristics would make this method become an attractive alternative for actual clinical diagnosis. (C) 2016 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier Sp. z o.o. All rights reserved.
Keyword:
DD-DWT
Non-linear
HE
FuzzyEn
GA-SVM
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.6
论文数:
944
被引数:
3.3K
机构
引用论文
Detection of epileptic electroencephalogram based on Permutation Entropy and Support Vector Machines基于排列熵和支持向量机的癫痫脑电检测
PREAI
分享收藏Hypertension Increases the Risk of Cerebral Microbleed in the Territory of Posterior Cerebral Artery: A Study of the Association of Microbleeds Categorized on a Basis of Vascular Territories and Cardiovascular Risk Factors高血压增加大脑后动脉区域脑微出血的风险: 基于血管区域和心血管危险因素分类的微出血关联研究
PREAI
分享收藏Tissue-specific differential antitumour effect of molecular forms of fractalkine in a mouse model of metastatic colon cancer.png)
Gut
OAAI
GutIF0
OAAI分享收藏分享收藏
查看更多内容