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A New HOS-Based Blind Source Extraction Method to Extract μ Rhythms from EEG Signals

机译:一种新的基于HOS的盲源提取方法,可从EEG信号中提取μ节律

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摘要

The μ rhythm is a type of EEG rhythms, which usually occurs over the motor-sensory cortex of the brain. It is believed to reflect the limb movement and imaginary limb movement controlled by the brain, thus it is one of the important sources of BCI systems. In this paper, a new fixed-point BSE algorithm based on skewness is proposed to extract μ rhythms by the feature of asymmetric distribution. The local stability of the algorithm is also proved in this article. The results from simulations indicate that, for the μ rhythm extraction, the proposed skewness-based algorithm performs better than the negentropy-based FastlCA.
机译:μ节律是一种EEG节律,通常发生在大脑的运动感觉皮层上。据信它反映了大脑控制的肢体运动和虚构的肢体运动,因此它是BCI系统的重要来源之一。提出了一种基于偏度的定点BSE算法,该算法利用不对称分布特征提取μ节律。本文还证明了该算法的局部稳定性。仿真结果表明,对于μ节奏提取,所提出的基于偏度的算法比基于负熵的FastlCA具有更好的性能。

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