作　　者： (王伟）; (管强）; (林枫）;

机构地区： 三明学院信息工程学院,福建三明365004

出　　处： 《三明学院学报》 2017年第4期25-33,共9页

摘　　要： 采用小波包分析法提取正常脑电波和发病脑电波的特征,构造特征向量,利用判别分析和聚类分析对脑电疾病特征进行判别分析和诊断分析。对三明市第一人民医院临床脑电数据进行实证分析,验证方法的实用性、准确性、高效性,为医生临床诊断发病区域提供科学依据。 In this paper, the wavelet packet analysis method is used to extract the feature of normal brain waves and the onset brain waves and construct the feature vector. Meantime, discriminant analysis and cluster analysis are used to identify patient＇s disease with EEG features. The empirical analysis is performed based on the clinical EEG data of the First People＇s Hospital of Sanming City in order to verify the method＇s practicability, accuracy and efficiency. The method can provide scientific basis for the clinical diagnosis of the doctor.

关 键 词： 脑电波信号 小波包分析 均值检验 判别分析 聚类分析