HUMAN SEIZURE DETECTION USING QUADRATIC RENYI ENTROPY

被引:0
|
作者
Feltane, Amal [1 ]
Bartels, G. F. Boudreaux [1 ]
Gaitanis, John [2 ]
Boudria, Yacine [1 ]
Besio, Walter [1 ]
机构
[1] Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA
[2] Brown Univ, Dept Neurol, Alpert Med Sch, Providence, RI 02912 USA
关键词
EMPIRICAL MODE DECOMPOSITION; ARTIFICIAL NEURAL-NETWORKS; EEG;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this study, the quadratic Renyi entropy is applied for seizure detection from human electroencephalography (EEG) signals. Quadratic Renyi entropy was combined with two different methods; the empirical mode decomposition (EMD) and discrete wavelet transform (DWT). The use of these two methods is justified since EEGs are non-linear and non-stationary signals. First, the EEG signal is decomposed into sub-signals using the EMD method or the DWT. Then, the quadratic Renyi entropy is used as an input feature. The k-nearest neighbor (k-NN) classifier algorithm extracted the features with 99.5%-100% accuracy.
引用
收藏
页码:815 / 818
页数:4
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