School of Precision Instruments and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, People's Republic of China.
J Neural Eng. 2010 Aug;7(4):046008. doi: 10.1088/1741-2560/7/4/046008. Epub 2010 Jun 23.
In this study, we proposed and evaluated the use of the empirical mode decomposition (EMD) technique combined with phase synchronization analysis to investigate the human brain synchrony of the supplementary motor area (SMA) and primary motor area (M1) during complex motor imagination of combined body and limb action. We separated the EEG data of the SMA and M1 into intrinsic mode functions (IMFs) using the EMD method and determined the characteristic IMFs by power spectral density (PSD) analysis. Thereafter, the instantaneous phases of the characteristic IMFs were obtained by the Hilbert transformation, and the single-trial phase-locking value (PLV) features for brain synchrony measurement between the SMA and M1 were investigated separately. The classification performance suggests that the proposed approach is effective for phase synchronization analysis and is promising for the application of a brain-computer interface in motor nerve reconstruction of the lower limbs.
在这项研究中,我们提出并评估了使用经验模态分解(EMD)技术结合相位同步分析来研究补充运动区(SMA)和初级运动区(M1)在联合身体和肢体动作的复杂运动想象期间的人类大脑同步性。我们使用 EMD 方法将 SMA 和 M1 的 EEG 数据分离成固有模态函数(IMF),并通过功率谱密度(PSD)分析确定特征 IMF。然后,通过希尔伯特变换获得特征 IMF 的瞬时相位,并分别研究 SMA 和 M1 之间脑同步测量的单试相位锁定值(PLV)特征。分类性能表明,所提出的方法对于相位同步分析是有效的,并且有望在下肢运动神经重建的脑机接口应用中得到应用。