Seizure-specific wavelet (Seizlet) design for epileptic seizure detection using CorrEntropy ellipse features based on seizure modulus maximas patterns

详细信息    查看全文

• 作者：Morteza Behnam^a ; ^b ; Hossein Pourghassem^a ; ^b ; ^{h_pourghasem@iaun.ac.ir}
• 关键词：Seizlet ; Seizure modulus maximas patterns ; Honeybee hive optimization ; CorrEntropy ellipse features ; Cone of influence map
• 刊名：Journal of Neuroscience Methods
• 出版年：2017
• 出版时间：30 January 2017
• 年：2017
• 卷：276
• 期：Complete
• 页码：84-107
• 全文大小：11391 K
• 卷排序：276

文摘

We design a discrete seizure-specific wavelet (Seizlet) to model the seizure signals. Four patterns are designed by Seizlet cone of influence map and modulus maximas lines. Features are defined by mapping CIM series from patterns and fitted conic ellipse. Features are tuned by Honeybee Hive optimization with LVRA and Elman neural network. 7-channel seizure signals are detected by AdaBoost classifiers in a cascade structure.