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A Study of Non-Gaussian Properties in Emotional EEG in Stroke Using Higher-Order Statistics

机译:使用高阶统计研究中风中情绪脑梗死中的非高斯性质研究

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The stroke patients often suffered from emotional disturbances, and this leads to perceive emotions differently than normal control subjects; the emotional impairment of the stroke patients can be effectively analyzed using EEG signal. The EEG signal has been known to have non-Gaussian properties, and the non-Gaussianity characteristics of the EEG differ under different emotional states. The analysis of non-Gaussianity in EEG signal was performed by using higher-order statistics measures such as the skewness and kurtosis. In this study, the non-Gaussianity was examined in the emotional EEG signal of stroke patients and normal control subjects. The estimation of the emotional EEG distribution from the results was symmetrically non-Gaussian for both stroke and normal groups. Particularly, it was found that the normal subjects have more non-Gaussian EEG distribution than the stroke patients.
机译:卒中患者经常遭受情绪障碍,这导致了与正常对照科目不同的情绪;使用脑电图,可以有效地分析中风患者的情绪损害。已知EEG信号具有非高斯性质,并且脑电图的非高斯特征在不同的情绪状态下不同。通过使用高阶统计测量(例如抗斜肌等)进行EEG信号中的非高斯分析。在这项研究中,在卒中患者的情绪脑电图信号和正常对照对象中检查了非高斯。从结果的情绪EEG分布的估计对于中风和正常组来说是对称的非高斯。特别是,发现正常受试者具有比中风患者更多的非高斯脑电图分布。

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