传感技术学报2018，Vol.31Issue(6)：904-914,11.DOI:10.3969/j.issn.1004-1699.2018.06.016
基于多元经验模态分解-传递熵的脑肌电信号耦合分析
Functional Coupling Analyses of EEG and EMG Based on Multivariate Empirical Mode Decomposition
摘要
Abstract
Functional corticomuscular coupling ( FCMC) is the interaction between the cerebral cortex and muscles. The multi-scale coupling characteristics of the Electroencephalography(EEG)and electromyography(EMG)signals can reflect the multiple temporal and spatial function of the cortex-muscle. The multivariate empirical modal decomposition (MEMD) and transfer entropy ( TE ) are combined to construct a MEMD-TE model, applied to analysis coupling between cortical and muscle activities. Firstly, the EEG and EMG signals were pre-processed, and then the multivariate empirical modal decomposition algorithm was used to perform time-frequency scaling on the signals. Fi-nally,the entropy values were calculated on different scales,and nonlinear coupling characteristics were analyzed on different coupling direction ( EEG→EMG and EMG→EEG). EEG and EMG signals of 10 subjects were collected under static grip(5 kg,10 kg and 20 kg),experimental results show that the MEMD-TE value from EEG to EMG is higher than that from EMG to EEG in the high frequency band(40 Hz~75 Hz),and FCMC is bi-directional and has differences in the coupling strength of different coupling directions and bands. In addition,the significance test revelas no significant difference between the MEMD-TE values from EEG to EMG under different grip forces.关键词
脑肌电信号/皮层肌肉功能耦合/多元经验模态分解/传递熵Key words
EEG-EMG/functional corticomuscular coupling/multivariate empirical mode decomposition/transfer entropy分类
信息技术与安全科学引用本文复制引用
马鹏刚,佘青山,高云园,张启忠,罗志增..基于多元经验模态分解-传递熵的脑肌电信号耦合分析[J].传感技术学报,2018,31(6):904-914,11.基金项目
国家自然科学基金项目(61201302,61671197) （61201302,61671197）
浙江省自然科学基金项目(LY15F010009) （LY15F010009）
