经穴电刺激诱发的脑-肌电信号相干性研究
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摘要
为探索自主动作和穴位电刺激诱发的大脑皮层活动与肌肉收缩之间的功能耦合作用,设计穴位电刺激和自主动作两种实验模式,分别采集对应的脑电信号和表面肌电信号,对信号进行预处理得到纯净的诱发脑电和肌电信号.然后进行小波变换,获得信号的小波谱和小波交叉谱,计算小波相干系数,分析脑电和肌电信号的时-频相干特性.结果表明:穴位电刺激诱发的脑-肌电相干性主要集中在15~25 Hz信号频段,对应于大脑β节律;而自主动作下的脑-肌电相干性集中在30~36Hz频段,对应于大脑γ节律;不同导联的脑-肌电信号相干特性,表明穴位电刺激诱发的腕部肌肉动作与对侧大脑运动区相干性最强.该研究为运动功能康复和智能假肢开发奠定了基础.
To explore coupling function between cerebral cortex activity and muscle contractions under the voluntary movement and the acupoint electrical stimulation,experimental models of the electrical stimulation and voluntary movement were designed to collect signals of electroencephalogram(EEG)and electromyography(EMG)respectively,and to get the evoked signals by doing data preprocessing.Then,wavelet spectral and cross wavelet spectrum of those signals were obtained by Wavelet Transform,wavelet coherence coefficient was calculated,and time-frequency coherence characteristics of EEG and EMG were analyzed.It is shown that EEG-EMG coherence,induced by acupoint electrical stimulation,mainly concentrates on 15~25Hz signal spectrum,corresponding to theβrhythm of EEG.However,EEG-EMG coherence,under the voluntary movement,concentrates on 30~36Hz signal spectrum,corresponding to theγrhythm of EEG.The signal coherence from different leads of EEG and EMG signals shows that wrist muscle action has strongest coherence with the contralateral motor area of brain while induced by acupoint electrical stimulation.The research laid a solid foundation for motor function recovery and intelligent prosthetic development.
To explore coupling function between cerebral cortex activity and muscle contractions under the voluntary movement and the acupoint electrical stimulation,experimental models of the electrical stimulation and voluntary movement were designed to collect signals of electroencephalogram(EEG)and electromyography(EMG)respectively,and to get the evoked signals by doing data preprocessing.Then,wavelet spectral and cross wavelet spectrum of those signals were obtained by Wavelet Transform,wavelet coherence coefficient was calculated,and time-frequency coherence characteristics of EEG and EMG were analyzed.It is shown that EEG-EMG coherence,induced by acupoint electrical stimulation,mainly concentrates on 15~25Hz signal spectrum,corresponding to theβrhythm of EEG.However,EEG-EMG coherence,under the voluntary movement,concentrates on 30~36Hz signal spectrum,corresponding to theγrhythm of EEG.The signal coherence from different leads of EEG and EMG signals shows that wrist muscle action has strongest coherence with the contralateral motor area of brain while induced by acupoint electrical stimulation.The research laid a solid foundation for motor function recovery and intelligent prosthetic development.
引文
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[2]纪仲秋,李旭龙.电刺激穴位按摩对局部运动疲劳后姿势控制能力恢复的影响[J].医用生物力学,2013,28(3):284-290.Ji Zhongqiu,Li Xulong.Recovery effect of postural control by electrical stimulation acupointmassage after local muscle fatigue[J].Journal of Medical Biomechanics,2013,28(3):284-290.(in Chinese)
[3]Fabrizio V,Claudio Del Percio,Nicola Marzano,et al.Functional cortico-muscular coupling during upright standing in athletes and nonathletes[J].ACoherence Electroencephalographic-Electromyographic Study.Behavioral Neuroscience,2008,122(1):917-927.
[4]Braun C,Staudt M,Schmitt C,et al.Crossedcortico-spinal motor control after capsular stroke[J].The European journal of neuroscience,2007,25(9):2935-2945.
[5]吴瑛,马海峰.穴位和非穴位刺激影响运动员神经传导速度的实验研究[J].上海体育学院学报,2008(3):46-48+66.Wu Ying,Ma Haifeng.Experimental research on effect of acupuncture pointand non-acupuncture point stimulations on athletes motorius conduction velocity[J].Journal of Shang hai Universit y of Sport,2008(3):46-48+66.(in Chinese)
[6]马培培,陈迎亚,杜义浩,等.中风康复运动中脑电-肌电相干性分析[J].生物医学工程学杂志,2014(5):971-977.Ma Peipei,Cheng Yingya,Du Yihao,et al.Analysis of corticomuscular coherence during rehabilitation exercises after stroke[J].Journal of Biomedical Engineering,2014(5):971-977.(in Chinese)
[7]Tuncel D,Dizibuyuk A,Kiymik M K,et al.Time frequency based coherence analysis between EEGand EMG activities in fatigue duration[J].J Med Syst.,2010,34:131-138.
[8]崔若飞.汽车驾驶员脑氧信号的近红外光谱法检测及小波相干性分析[D].济南:山东大学,2014.