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Comparison of the AMICA and the InfoMax algorithm for the reduction of electromyogenic artifacts in EEG data

机译:比较AMICA和InfoMax算法以减少脑电数据中的肌电伪影

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摘要

Electromyogenic or muscle artifacts constitute a major problem in studies involving electroencephalography (EEG) measurements. This is because the rather low signal activity of the brain is overlaid by comparably high signal activity of muscles, especially neck muscles. Hence, recording an artifact-free EEG signal during movement or physical exercise is not, to the best knowledge of the authors, feasible at the moment. Nevertheless, EEG measurements are used in a variety of different fields like diagnosing epilepsy and other brain related diseases or in biofeedback for athletes.
机译:在涉及脑电图(EEG)测量的研究中,肌原性或肌肉伪影构成了一个主要问题。这是因为大脑相对较低的信号活动被肌肉(尤其是颈部肌肉)相对较高的信号活动所覆盖。因此,据作者所知,在运动或体育锻炼过程中记录无伪像的EEG信号目前尚不可行。尽管如此,脑电图测量仍用于各种不同的领域,例如诊断癫痫和其他与大脑有关的疾病,或用于运动员的生物反馈。

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