摘要
本文将多元经验模态分解(MEMD)与鲁棒时变广义偏定向相干性(rTV-gPDC)引入皮层肌肉耦合分析中,探索脑肌电之间线性和非线性耦合关系。首先同步采集8名健康志愿者在静态握力(5 kg、10 kg、20 kg)下的三通道脑电(EEG)和肌电(EMG)信号,接着采用MEMD对信号进行时-频尺度化,最后同时计算不同耦合方向(EEG→EMG和EMG→EEG)上的rTV-gPDC线性和非线性值。实验结果表明静态握力输出时,皮层肌肉耦合主要反映在beta和gamma频段,其中EEG→EMG方向的耦合强度略高于EMG→EEG方向的耦合强度,且随着左右手握力增加,EEG→EMG和EMG→EEG方向的耦合强度同时增加。此外脑肌电耦合中同时存在线性和非线性因果关系。本文方法能够定量刻画不同握力下三个脑肌电通道之间的线性和非线性交互影响,可为研究运动功能障碍及康复评价提供有效的生理参数指标。
In this paper,multivariate empirical mode decomposition(MEMD)and robust time-varying generalized partial orientation coherence(rTV-gPDC)are introduced into the corticomuscular coupling analysis to explore the linear and nonlinear relationships between electroencephalogram(EEG)and electromyography(EMG)signals.First,the three channels EEG and EMG signals under static grip(5 kg,10 kg,20 kg)of 8 healthy volunteers were collected synchronously,and then the time-frequency scaling of signals was carried out by the multivariate empirical mode decomposition algorithm.Finally,the linear and nonlinear values of rTV-gPDC in the different coupling directions(EEG→EMG and EMG→EEG)were calculated simultaneously.Experimental results show that the corticomuscular coupling between EEG and EMG signals is mainly reflected in the beta and gamma bands during static grip output.The coupling strength of EEG→EMG direction is slightly stronger than EMG→EEG direction and the coupling strength of EEG→EMG and EMG→EEG increases simultaneously as the grip strength of the left and right hands increases.Moreover,there are linear and nonlinear causal relationships between EEG and EMG signals.The method can quantitatively describe the linear and nonlinear interaction between the three channels of EEG and EMG signals under different grip strengths,and it may provide a theoretical basis for the study of motor function dysfunction and evaluation of motor function during rehabilitation in the future.
作者
张敏
佘青山
张波涛
吴秋轩
范影乐
ZHANG Min;SHE Qingshan;ZHANG Botao;WU Qiuxuan;FAN Yingle(School of Automation,Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2020年第3期327-334,共8页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(61871427)
省重点研发计划项目(2019C04018)。
关键词
脑肌电信号
皮层肌肉功能耦合
多元经验模态分解
鲁棒时变广义偏定向相干性
EEG-EMG
functional corticomuscular coupling
multivariate empirical mode decomposition
robust Time-Varying generalized Partial Directed Coherence
