[Synchronous analysis of corticomuscular coherence based on Gabor wavelet-transfer entropy]
- PMID: 29761978
- PMCID: PMC9935337
- DOI: 10.7507/1001-5515.201608018
[Synchronous analysis of corticomuscular coherence based on Gabor wavelet-transfer entropy]
Abstract
Synchronization analysis of electroencephalogram (EEG) and electromyogram (EMG) could reveal the functional corticomuscular coupling (FCMC) during the motor task in human. A novel method combining Gabor wavelet and transfer entropy (Gabor-TE) is proposed to quantitatively analyze the nonlinearly synchronous corticomuscular function coupling and direction characteristics under different steady-state force. Firstly, the Gabor wavelet transform method was used to acquire the local frequency-band signals of the EEG and EMG signals recorded from nine healthy controls simultaneously during performing grip task with four different steady-state forces. Secondly, the TE of local frequency-band was calculated and the unit area index of the transfer ( ATE) was defined to quantitatively analyze the synchronous corticomuscular function coupling and direction characteristics under steady-state force. Lastly, the effect of EEG and EMG signal power spectrum on Gabor-TE analysis was explored. The results showed that the coupling strength in the beta band was stronger in EEG→EMG direction than in EMG→EEG direction, and the ATE values in the beta band in EEG→EMG direction decreased with the force increasing. It is also shown that the difference in TE values of gamma band present a varying regularity as the increase of force in both directions. In addition, EMG power spectrum was significantly correlated with the result of Gabor-TE inspecific frequency band. The results of our study confirmed that Gabor-TE can quantitatively describe the nonlinearly synchronous corticomuscular function coupling in both local frequency band and information transmission. The analysis of FCMC provides basic information for exploring the motor control and the evaluation of clinical rehabilitation.
人体运动中脑电(EEG)信号和肌电(EMG)信号间的同步特征能够反映皮层肌肉间功能耦合 (FCMC) 的关系。本文将 Gabor 小波和传递熵 (TE) 结合,提出一种新的方法(Gabor-TE)用以定量分析不同恒定握力下 EEG-EMG 信号间的非线性同步耦合特征及方向特性。本研究首先选取 9 名健康受试者在 4 种不同恒定握力下的 EEG、EMG 信号,并以 Gabor 小波变换进行局部分解;然后计算频带 TE 值并定义单位传递面积指标 ( ATE),分析恒定握力下 EEG-EMG 信号的局部频段同步特征及方向特性;最后探究 EEG 信号和 EMG 信号功率谱对 Gabor-TE 方法分析结果的影响。本文研究结果表明:恒定握力下,β 频段 EEG→EMG 方向 TE 值高于 EMG→EEG 方向,且随握力水平增加 EEG→EMG 方向上 β 频段 ATE 值降低;γ 频段 TE 值在 EMG→EEG 和 EEG→EMG 方向上的差异随握力增加而呈现出一定的变化规律;EMG 功率谱与特征频段 TE 结果强相关。本文试验结果表明,Gabor-TE 方法能定性、定量描述 EEG-EMG 信号在局部频带和信息传递上的非线性同步耦合特征,今后或可为研究运动控制及患者康复评价提供一定的理论依据。.
Keywords: Gabor wavelet transform; corticomuscular coupling; local frequency-band; steady-state force; transfer entropy.
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