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Differentiating Between Psychogenic Nonepileptic Seizures and Epilepsy Based on Common Spatial Pattern of Weighted EEG Resting Networks

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机构: [1]Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China [2]Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China [3]Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, and also with Cuban Neuroscience Center, Habana 6 CP 10600, Cuba [4]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China, and also with Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
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关键词: Brain network common spatial pattern of brain network topology psychogenic nonepileptic seizures (PNES) resting scalp EEG

摘要:
Discriminating psychogenic nonepileptic seizures (PNES) from epilepsy is challenging, and a reliable and automatic classification remains elusive. In this study, we develop an approach for discriminating between PNES and epilepsy using the common spatial pattern extracted from the brain network topology (SPN). The study reveals that 92% accuracy, 100% sensitivity, and 80% specificity were reached for the classification between PNES and focal epilepsy. The newly developed SPN of resting EEG may be a promising tool to mine implicit information that can be used to differentiate PNES from epilepsy.

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出版当年[2013]版:
大类 | 2 区 工程技术
小类 | 3 区 工程:生物医学
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 工程:生物医学
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出版当年[2012]版:
Q2 ENGINEERING, BIOMEDICAL
最新[2023]版:
Q2 ENGINEERING, BIOMEDICAL

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第一作者机构: [1]Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
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