论文标题
通过添加EMG来源（ERASE）的去除（EMG） - 一种基于ICA的新型算法，用于从EEG中去除肌电伪影 - 第2部分
Electromyogram (EMG) Removal by Adding Sources of EMG (ERASE) -- A novel ICA-based algorithm for removing myoelectric artifacts from EEG -- Part 2
论文作者
论文摘要
从具有半晶状体切除术的创伤性脑损伤（TBI）患者中提取与运动相关的高γ（80-160 Hz）在脑电图（EEG）中提取，由于与表面骨膜（EMG）的混淆带宽重叠，因此仍然具有挑战性。在第1部分中，我们描述了一种增强的独立组件分析（ICA）方法，用于去除EEG中的EMG伪像，并通过添加EMG（ERASE）来称为EMG降低。在这里，我们测试了六名Hemicraniectomies患者在执行拇指屈曲任务时记录的EEG擦除。 ERASE的平均值为52 +/- 12％（平均+/- S.E.M）（最大73％）EMG伪影。相比之下，常规ICA除去了EEG的EMG伪像的平均值27 +/- 19 \％（平均值+/- s.e.m）。特别是，在擦除擦除后对侧手运动皮层区域内的对侧手运动皮层区域中，高γ同步得到了显着改善。我们计算了每个通道上EEG高γ的分形维度（FD）。我们发现，在施加擦除后，高γ的相对FD与半辐射切除术相对于半骨切除术，与手指屈曲力的振幅密切相关。结果表明，与拇指屈曲相关的电极之间的显着相关系数平均为0.76，而非肺炎颅骨切除术区域的同源电极的系数接近0。在所有受试者中，平均83％的电极与力与施加的电极显着相关。常规ICA之后，在半晶状体切除术中只有19％的具有显着相关性的电极。这些结果表明，新方法在手指运动激活过程中分离了电生理特征，同时选择性地去除混杂的EMG伪影。
Extraction of the movement-related high-gamma (80 - 160 Hz) in electroencephalogram (EEG) from traumatic brain injury (TBI) patients who have had hemicraniectomies, remains challenging due to a confounding bandwidth overlap with surface electromyogram (EMG) artifacts related to facial and head movements. In part 1, we described an augmented independent component analysis (ICA) approach for removal of EMG artifacts from EEG, and referred to as EMG Reduction by Adding Sources of EMG (ERASE). Here, we tested ERASE on EEG recorded from six TBI patients with hemicraniectomies while they performed a thumb flexion task. ERASE removed a mean of 52 +/- 12% (mean +/- S.E.M) (maximum 73%) of EMG artifacts. In contrast, conventional ICA removed a mean of 27 +/- 19\% (mean +/- S.E.M) of EMG artifacts from EEG. In particular, high-gamma synchronization was significantly improved in the contralateral hand motor cortex area within the hemicraniectomy site after ERASE was applied. We computed fractal dimension (FD) of EEG high-gamma on each channel. We found relative FD of high-gamma over hemicraniectomy after applying ERASE were strongly correlated to the amplitude of finger flexion force. Results showed that significant correlation coefficients across the electrodes related to thumb flexion averaged 0.76, while the coefficients across the homologous electrodes in non-hemicraniectomy areas were nearly 0. Across all subjects, an average of 83% of electrodes significantly correlated with force was located in the hemicraniectomy areas after applying ERASE. After conventional ICA, only 19% of electrodes with significant correlations were located in the hemicraniectomy. These results indicated that the new approach isolated electrophysiological features during finger motor activation while selectively removing confounding EMG artifacts.
