北京生物医学工程2011，Vol.30Issue(4)：381-386,6.DOI:10.3969/j.issn.1002-3208.2011.04.12
基于EMD和Hilbert变换的自发脑电信号特征提取
EEG Feature Extraction Based on Empirical Mode Decomposition and Hilbert Transform in Brain Computer Interface
摘要
Abstract
In the study of brain computer interfaces , a method based on empirical mode decomposition (EMD) and Hilbert transformation was proposed. The method was used for the feature extraction of electroencephalogram. In this method, the basis function was selected automatically according to the local features of signal during the transforming process, the Hilbert spectrum was obtained in each period, and the statistical characteristics in time-frequency window were considered as features. Then the optimal feature sets were formed by the Fisher distance rule and put into the classification. The performance of the eigenvector was evaluated by separability and recognition accuracy with the data set of BCI 2003 competition , and classification results proved the effectiveness of the proposed method.关键词
脑机接口/脑电信号/经典模态分解/希尔伯特变换/特征提取Key words
brain computer interface / electroencephalogram / empirical mode decomposition / Hilbert transformation / feature extraction分类
医药卫生引用本文复制引用
吴婷,颜国正,钱炳锋..基于EMD和Hilbert变换的自发脑电信号特征提取[J].北京生物医学工程,2011,30(4):381-386,6.基金项目
上海市教育委员会重点学科建设项目(J51902)、上海市教委晨光计划项目(09CG69)资助 （J51902）
