Goncharova I I, McFarland D J, Vaughan T M, Wolpaw J R
Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health and State University of New York, Empire State Plaza, P.O. Box 509, Albany, NY 12201-0509, USA.
Clin Neurophysiol. 2003 Sep;114(9):1580-93. doi: 10.1016/s1388-2457(03)00093-2.
Electromyogram (EMG) contamination is often a problem in electroencephalogram (EEG) recording, particularly, for those applications such as EEG-based brain-computer interfaces that rely on automated measurements of EEG features. As an essential prelude to developing methods for recognizing and eliminating EMG contamination of EEG, this study defines the spectral and topographical characteristics of frontalis and temporalis muscle EMG over the entire scalp. It describes both average data and the range of individual differences.
In 25 healthy adults, signals from 64 scalp and 4 facial locations were recorded during relaxation and during defined (15, 30, or 70% of maximum) contractions of frontalis or temporalis muscles.
In the average data, EMG had a broad frequency distribution from 0 to >200 Hz. Amplitude was greatest at 20-30 Hz frontally and 40-80 Hz temporally. Temporalis spectra also showed a smaller peak around 20 Hz. These spectral components attenuated and broadened centrally. Even with weak (15%) contraction, EMG was detectable (P<0.001) near the vertex at frequencies >12 Hz in the average data and >8 Hz in some individuals.
Frontalis or temporalis muscle EMG recorded from the scalp has spectral and topographical features that vary substantially across individuals. EMG spectra often have peaks in the beta frequency range that resemble EEG beta peaks.
While EMG contamination is greatest at the periphery of the scalp near the active muscles, even weak contractions can produce EMG that obscures or mimics EEG alpha, mu, or beta rhythms over the entire scalp. Recognition and elimination of this contamination is likely to require recording from an appropriate set of peripheral scalp locations.
肌电图(EMG)干扰在脑电图(EEG)记录中常常是个问题,特别是对于那些诸如基于EEG的脑机接口等依赖EEG特征自动测量的应用而言。作为开发识别和消除EEG中EMG干扰方法的重要前奏,本研究定义了整个头皮上额肌和颞肌EMG的频谱和地形特征。它描述了平均数据以及个体差异范围。
在25名健康成年人中,在放松状态以及额肌或颞肌进行规定的(最大收缩力的15%、30%或70%)收缩期间,记录来自64个头皮位置和4个面部位置的信号。
在平均数据中,EMG具有从0到>200 Hz的广泛频率分布。额部在20 - 30 Hz时幅度最大,颞部在40 - 80 Hz时幅度最大。颞肌频谱在20 Hz左右也显示出一个较小的峰值。这些频谱成分在头皮中央衰减并展宽。即使是微弱的(15%)收缩,在平均数据中,顶点附近频率>12 Hz时可检测到EMG(P<0.001),在一些个体中频率>8 Hz时可检测到。
从头皮记录的额肌或颞肌EMG具有频谱和地形特征,个体间差异很大。EMG频谱在β频率范围内通常有峰值,类似于EEG的β波峰。
虽然EMG干扰在靠近活动肌肉的头皮周边最大,但即使是微弱收缩也会产生EMG,其会在整个头皮上掩盖或模仿EEG的α、μ或β节律。识别和消除这种干扰可能需要从一组合适的头皮周边位置进行记录。