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The Study of Classification of Motor Imaginaries Based on Kurtosis of EEG

机译:基于脑电峰度的运动想象者分类研究

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In this paper, the kurtosis-based method for the classification of mental activities is proposed. The EEG signals were recorded during imagination of left or right hand movement. The kurtosis of EEG and its dynamic properties with respect to time are analyzed. The experiment results show that the kurtosis can reflect the EEG pattern changes of different motor imageries. According to the analysis and experiment results, a kurtosis based classifier for the classification of left and right movement imagination is designed. This classifier can achieves near 90% correct rate. As the kurtosis is computationally less demanding and can also be estimated in on-line way, so the new method proposed in this paper has the practicability in the application of brain-computer interface.
机译:本文提出了一种基于峰度的心理活动分类方法。在想象左手或右手运动期间记录了EEG信号。分析了脑电图的峰度及其相对于时间的动态特性。实验结果表明,峰度可以反映不同运动图像的脑电图模式变化。根据分析和实验结果,设计了一种基于峰度的左,右运动想象力分类器。该分类器可以达到接近90%的正确率。由于峰度对计算的要求不高,并且也可以在线估算,因此本文提出的新方法在脑机接口的应用中具有实用性。

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