基于变尺度符号传递熵的多通道脑肌电信号耦合分析高云园;任磊磊;周旭;张启忠;张迎春【摘要】在运动控制中,脑肌电耦合强度可以反映大脑皮层和运动肌肉之间的联系.传统的时间序列符号化方法容易混淆原始信号,丢失信号的动态特性.因此,提出可变尺度参数的符号传递熵,对上肢不同握力下的皮层脑电和表面肌电信号进行多通道耦合性分析,进而提出一种耦合强度的表示方法,对脑肌电耦合强度进行定量分析.首先,分析并比较尺度参数对脑肌电传递熵的影响,并选择优化的尺度进行符号化传递熵的计算;其次,针对不同握力下多通道脑肌电信号的分析,验证大脑运动区C3、C4通道的脑电在运动控制中占主导地位以及大脑的对侧控制机制.实验中还发现,随着握力的增强,肌电到脑电的传递熵有增大趋势,右手(惯用手)脑电到肌电的传递熵较左手的高,同时随着输出力量的增强,脑肌电的双向平均耦合强度也增大.结果分析显示:5、10、20 kg握力下,EMG→EEG方向的左手耦合强度分别为0.033 0±0.005 8、0.037 3±0.0040、0.045 1±0.005 5,右手耦合强度分别为0.0352±0.0029、0.0432±0.0035、0.0603±0.001 8,除左手5和10 kg握力间不存在显著性差异,其余都具有显著性差异(P＜0.05);EEG→EMG方向左手耦合强度分别为0.0253±0.0047、0.037 9±0.002 6、0.048 1土0.006 8,右手耦合强度分别为0.033 3±0.004 1、0.051 0±0.005 7、0.064 9±0.008 5,不同握力间均有显著性差异.研究结果表明:皮层肌肉功能耦合具有双向性,而且耦合强度在通道和握力不同时有差异.变尺度传递熵可用于定量描述大脑皮层与神经肌肉组织之间的非线性同步特征及信息交互.%The coupling strength (CS) of the electroencephalogram (EEG) and electromyogram (EMG) reflects the connection between the cerebral cortex and active muscles in motion control.Conventional symbolic transfer entropy analysis (STE) methods arelimited to effectively reveal the dynamic characteristics.In order to quantitatively analyze multi-channel EEG and EMG coupling,a variable scale symbolic transfer entropy (VSP-STE) analysis approach was proposed in this paper,and a CS expressive method was presented to quantitatively measure the corticomuscular CS of EEG and EMG signals during grip tasks.The influence of the scale parameter on EEG-EMG transfer entropy was first analyzed and compared at different grip force levels.The optimized scale parameter was then applied to the STE calculation in experimental data analysis.Results demonstrated the dominance of the C3 and C4 EEG channels in motion control,as well as the contralateral control mechanism of the brain.In addition,the premotor cortex (FC5 and FC6) also played an important role in corticomuscular coupling.Results showed that the EMG→EEG transfer entropy increased as the grip force increased (5,10,20 kg),and the right hand (dominant hand) showed higher EEG→EMG transfer entropy than the left hand in all the 3 subjects.The two-way (EEG→EMG,EMG→EEG) coupli ng strengths were also increased as the grip force increased.The statistical analysis showed that at 5,10,20 kg grip force levels,EMG→ EEG coupling strength of left hand was 0.0330 ±0.0058,0.0373 ± 0.0040,0.0451 ± 0.0055 respectively,and that of right han d was 0.0352 ± 0.0029,0.0432 ± 0.0035,0.0603 ± 0.0018 respectively.There was a significant difference (p ＜ 0.05) of coupling strength,except for that between 5 kg and 10 kg of grip force in left hand.For EEG→EMG,coupling strength of left hand is 0.0253 ± 0.0047,0.0379 ±0.0026,0.0481±0.0068,and that of right hand is 0.0333 ±0.0041,0.0510±0.0057,and 0.0649 ±0.0085 respectively.The difference of coupling strength was significant for all.In conclusion,our results show that corticomuscular coupling is a two-way process and the coupling strength varies with different channels and gripping strength.VSP-STE can be used to describe the nonlinear synchronizing characteristics and information interaction of the cerebral cortex and neuromuscular tissue.【期刊名称】《中国生物医学工程学报》【年(卷),期】2018(037)001【总页数】9页(P8-16)【关键词】耦合;多通道;符号传递熵;脑肌电信号【作者】高云园;任磊磊;周旭;张启忠;张迎春【作者单位】杭州电子科技大学自动化学院机器人研究所,杭州310018;杭州电子科技大学自动化学院机器人研究所,杭州310018;杭州电子科技大学自动化学院机器人研究所,杭州310018;广东省工伤康复中心,广州510900;杭州电子科技大学自动化学院机器人研究所,杭州310018;广东省工伤康复中心,广州510900;休斯顿大学生物医学工程系,美国休斯顿77204【正文语种】中文【中图分类】R318引言脑电信号(electroencephalogram, EEG)是通过电极记录到的大脑神经群自发或者节律性活动所产生的信号，它反映了大脑功能区神经细胞群活动时的电位变化。
