首页> 外文会议>IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications >Functional Corticomuscular Coupling Based on Bivariate Empirical Mode Decomposition - Multiscale Transfer Entropy
【24h】

Functional Corticomuscular Coupling Based on Bivariate Empirical Mode Decomposition - Multiscale Transfer Entropy

机译:基于二元经验模态分解的功能性皮层耦合-多尺度传递熵

获取原文

摘要

The functional corticomuscular coupling (FCMC) is a physiological phenomenon to reflect the multilayered characteristics of the information interaction between electroencephalogram (EEG) and electromyographic (EMG) signals. The multilayered characteristics such as local frequency band, complex and multiscale between the brain and muscles are of great significance to understand the cooperative function of the motor-sensory neural network. Though the multiscale transfer entropy (MSTE) method can effectively describe the multiscale and complex characteristics of the coupling signals to some extent, it fails to describe the FCMC on the local frequency band. Therefore, in this study, we combined the bivariate empirical mode decomposition (BEMD) with the MSTE to construct a new model, named bivariate empirical mode decomposition-multiscale transfer entropy (BMTE), to quantify the synchronous coupling between EEG and EMG signals on the local frequency band at different scales. The results show that the FCMC is significant in both EEG→EMG and EMG → EEG directions at betal and beta2 bands during steady-state grip task. Meanwhile, the maximum coupling strength value at beta2 band on different scales alomost occur on the high scales (9–16 scales), and the significant value at betal band was on the lower time scale. Additionally, the coupling strength at gamma band in EEG→ EMG direction is also significant in the higher scale. The results show that the BMTE method can quantitatively describe the local frequency band and multiscale characteristics between the motor cortex and the contralateral muscle in motor control system. This study extends the relative researches on the FCMC.
机译:功能性皮质震荡耦合(FCMC)是一种生理现象,反映了脑电图(EEG)和肌电图(EMG)信号之间信息交互的多层特征。大脑和肌肉之间的局部频带,复杂和多尺度等多层特性对于理解运动感觉神经网络的协同功能具有重要意义。尽管多尺度传递熵(MSTE)方法可以在一定程度上有效地描述耦合信号的多尺度和复杂特性,但是它无法在本地频带上描述FCMC。因此,在这项研究中,我们将双变量经验模态分解(BEMD)与MSTE结合起来,构建了一个名为双变量经验模态分解-多尺度传递熵(BMTE)的模型,以量化脑电信号和EMG信号之间的同步耦合。不同规模的本地频段。结果表明,在稳态抓握任务期间,在betal和beta2波段,FCMC在EEG→EMG和EMG→EEG方向上均很显着。同时,不同尺度上β2波段的最大耦合强度值最高出现在高尺度(9–16尺度)上,而贝塔尔波段的显着值则在较低的时间尺度上。另外,在较高范围内,EEG→EMG方向上的伽马带上的耦合强度也很重要。结果表明,BMTE方法可以定量地描述运动控制系统中运动皮层与对侧肌肉之间的局部频带和多尺度特征。该研究扩展了FCMC的相关研究。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号