摘要
研究表明,神经精神疾病患者的临床表现与其大脑功能网络连接异常是相关的。心因性非癫痫(PNES)是一种心理疾病,不具有特征性的癫痫放电表现,是临床诊断上的一个难点。本文基于采集的脑电图(EEG)信号,利用网络分析方法,发现PNES患者前额与枕顶脑区之间的网络连接强度较正常组减弱。并且,将网络属性作为特征,利用线性判别分析(LDA)可对PNES患者和对照组获得85%的分类准确率,为临床诊断提供具有实际意义的价值信息。
Studies have shown that the clinical manifestation of patients with neuropsychiatric disorders might be related to the abnormal connectivity of brain functions.Psychogenic non-epileptic seizures（PNES）are different from the conventional epileptic seizures due to the lack of the expected electroencephalographically epileptic changes in central nervous system,but are related to the presence of significant psychological factors.Diagnosis of PNES remains challenging.We found in the present work that the connectivity between the frontal and parieto-occipital in PNES was weaker than that of the controls by using network analysis based on electroencephalogram（EEG）signals.In addition,PNES were recognized by using the network properties as linear discriminant nalysis（LDA）input and classification accuracy was 85%.This study may provide a feasible tool for clinical diagnosis of PNES.
出处
《生物医学工程学杂志》
CAS
CSCD
北大核心
2015年第1期8-12,共5页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(61175117,31070881,31100745)
新世纪优秀人才项目资助(NCET-12-0089)
863重点项目资助(2012AA011601)
北京市科技计划项目资助(Z101107050210015)
关键词
脑电图
心因性非癫痫
网络分析
线性判别分析
electroencephalogram
psychogenic non-epileptic seizures
network analysis
linear discriminant analysis
