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θ节律在检测手指运动中的作用研究

Investigation of Theta Rhythm Effect in Detection of Finger Movement.

作者信息

Ketenci Seniha, Kayikcioglu Temel

机构信息

Department of Electrical and Electronics Engineering, Karadeniz Technical University, Trabzon, Turkey.

出版信息

J Exp Neurosci. 2019 Feb 19;13:1179069519828737. doi: 10.1177/1179069519828737. eCollection 2019.

Abstract

Movements cause changes in cortical rhythms emanating from the sensorimotor area. It is known that alpha and beta brainwaves take an important role of motor activity and motor imagery. Besides, theta rhythm is considered to carry substantial information about movement initiation and execution. In this study, effect of theta brainwave on movement detection was investigated in four-right handed participants who performed extensions with fingers of right hand using electroencephalography (EEG). Movement and rest epochs from continuous EEG record were extracted using muscle signals. Channels located over sensorimotor area were selected and referenced according to common average and Laplacian reference methods. Power spectral density function was used to display existence of theta band in frequency domain. To analyze theta, alpha and beta rhythms of the epochs individually and together, we filtered them to their interval range with Butterworth bandpass infinite filter before feature extraction and classification stages. Then, principal component analysis and Hjorth parameters were chosen to extract efficient features in the study aiming to investigate the effect of theta brainwaves on finger movement detection. According to classification accuracies using support vector machine classifier, alpha, beta, theta rhythms and also their different combinations were compared with each other. The performance of the epochs including alpha, beta and theta rhythms were the best and they were classified ~2% to 4% higher value in accuracy than the signals including only alpha and beta rhythms. According to this, it has proved that theta brainwave takes a role and makes contribution to motor activity.

摘要

运动可引起源自感觉运动区的皮层节律变化。已知α波和β波在运动活动和运动想象中发挥重要作用。此外,θ节律被认为携带有关运动起始和执行的大量信息。在本研究中,使用脑电图(EEG)对四名右利手参与者进行右手手指伸展动作时,研究了θ脑波对运动检测的影响。利用肌肉信号从连续脑电图记录中提取运动和休息时段。选择位于感觉运动区上方的通道,并根据公共平均参考法和拉普拉斯参考法进行参考。功率谱密度函数用于在频域中显示θ频段的存在。为了分别和共同分析这些时段的θ、α和β节律,在特征提取和分类阶段之前,我们使用巴特沃斯带通无限滤波器将它们滤波到各自的区间范围。然后,选择主成分分析和 Hjorth 参数在本研究中提取有效特征,旨在研究θ脑波对手指运动检测的影响。根据使用支持向量机分类器的分类准确率,将α、β、θ节律及其不同组合相互比较。包括α、β和θ节律的时段表现最佳,其分类准确率比仅包括α和β节律的信号高约2%至4%。据此,已证明θ脑波在运动活动中发挥作用并做出贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189a/6381427/1d975e83f261/10.1177_1179069519828737-fig1.jpg

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