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机译:使用头皮EEG跨频耦合特征对临床前癫痫发作状态进行分类
Institute of Biomaterials and Biomedical EngineeringUniversity of Toronto;
Institute of Biomaterials and Biomedical EngineeringUniversity of Toronto;
Department of Medicine (Neurology)Toronto Western Hospital;
Institute of Biomaterials and Biomedical Engineering, University of Toronto;
Institute of Biomaterials and Biomedical Engineering and the Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada;
Electroencephalography; Feature extraction; Training; Scalp; Testing; Continuous wavelet transforms; Couplings;
机译:相振幅跨频耦合对相移和偶发电位的敏感性:ECoG和头皮EEG数据中可能存在的寄生耦合
机译:使用基于小波的特征和SVM的单通道头皮EEG数据的癫痫癫痫发布分类
机译:成功的记忆编码与人类头皮记录的脑电图中额叶theta和后伽马振荡之间的交叉频率耦合增加有关
机译:在颅内脑电图记录中使用交叉频率耦合探测皮层兴奋性:一种预测癫痫发作的新方法
机译:基于非基于EEG的婴儿痉挛预测使用相位振荡频率耦合的深度学习网络
机译:临床发作前的头皮脑电图状态分类
机译:基于EMD的能量和分形特征对癫痫发作的低密度脑电图分类