一种改进的最大信息系数算法在脑卒中患者的皮质肌功能耦合分析中的应用  

An improved maximal information coefficient algorithm applied in the analysis of functional corticomuscular coupling for stroke patients

作　　者：梁铁[1,2] 张清愉 洪磊 刘晓光 董斌[1,3] 王洪瑞[1,2] 刘秀玲[1] LIANG Tie;ZHANG Qingyu;HONG Lei;LIU Xiaoguang;DONG Bin;WANG Hongrui;LIU Xiuling(School of Electronic and Information Engineering,Hebei University,Baoding,Hebei 071002,P.R.China;Institute of Electric Engineering,Yanshan University,Qinhuangdao,Hebei 066004,P.R.China;Development Planning Office,Afliated Hospital of Hebei University,Baoding,Hebei 071002,P.R.China)

机构地区：[1]河北大学电子信息工程学院,河北保定071002 [2]燕山大学电气工程学院,河北秦皇岛066004 [3]河北大学附属医院发展规划办公室,河北保定071002

出　　处：《生物医学工程学杂志》2021年第6期1154-1162,共9页Journal of Biomedical Engineering

基　　金：国家重点研发计划基金资助项目(2017YFB1401200);河北省自然科学基金资助项目(F2021201002);河北省高等学校科学技术研究项目(ZD2020146);河北大学实验室开放项目(sy202029)。

摘　　要：自主运动过程中,运动皮层和效应肌之间的功能耦合可以通过计算脑电(EEG)信号和表面肌电(sEMG)信号之间的耦合来量化。最大信息系数算法(MIC)被证明能够有效量化这种神经信号之间的耦合关系,然而实际使用中也存在计算耗时长的问题。为解决该问题,基于改进的K均值(K-means++)算法的高效聚类特性,本文提出了一种改进的MIC算法用以准确检测非线性时间序列之间的耦合强度。仿真结果表明,本文所提改进的MIC算法能够在不同噪声水平下快速而准确捕获非线性时间序列之间的耦合关系。基于脑卒中患者的右脚背屈试验结果表明,改进的MIC算法能准确捕获EEG信号和sEMG信号在特定频带上的耦合强度;相比健康对照组,脑卒中患者组的beta频段(14~30 Hz)和gamma频段(31~45 Hz)的皮质肌功能耦合(FCMC)显著更弱,beta频段MIC值与福格-迈尔评定量表(FMA)评分正相关。本研究所提算法有望成为脑卒中患者运动功能量化评估的新手段。The functional coupling between motor cortex and effector muscles during autonomic movement can be quantified by calculating the coupling between electroencephalogram(EEG)signal and surface electromyography(sEMG)signal.The maximal information coefficient(MIC)algorithm has been proved to be effective in quantifying the coupling relationship between neural signals,but it also has the problem of time-consuming calculations in actual use.To solve this problem,an improved MIC algorithm was proposed based on the efficient clustering characteristics of K-means++algorithm to accurately detect the coupling strength between nonlinear time series.Simulation results showed that the improved MIC algorithm proposed in this paper can capture the coupling relationship between nonlinear time series quickly and accurately under different noise levels.The results of right dorsiflexion experiments in stroke patients showed that the improved method could accurately capture the coupling strength of EEG signal and sEMG signal in the specific frequency band;Compared with the healthy controls,the functional corticomuscular coupling(FCMC)in beta(14-30 Hz)and gamma band(31-45 Hz)were significantly weaker in stroke patients,and the beta-band MIC values were positively correlated with the Fugl-Meyers assessment(FMA)scale scores.The method proposed in this study is hopeful to be a new method for quantitative assessment of motor function for stroke patients.

关 键 词：皮质肌功能耦合 最大信息系数 脑电图 表面肌电信号 脑卒中 

分 类 号：R743.3[医药卫生—神经病学与精神病学]