首页> 外文会议>2011 IEEE International Symposium on Medical Measurements and Applications >Analysis of absence seizure EEG via Permutation Entropy spatio-temporal clustering
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Analysis of absence seizure EEG via Permutation Entropy spatio-temporal clustering

机译:排列熵时空聚类分析失神发作脑电图

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The genesis of epileptic seizures is nowadays still mostly unknown. The hypothesis that most of scientist share is that an abnormal synchronization of different groups of neurons seems to trigger a recruitment mechanism that leads the brain to the seizure in order to reset this abnormal condition. If this is the case, a gradual transformation of the characteristics of the EEG can be hypothesized. It is therefore necessary to find a parameter that is able to measure the synchronization level in the EEG and, since the spatial dimension has to be taken into account if we aim to find out how the different areas in the brain recruit each other to develop the seizure, a spatio-temporal analysis of this parameter has to be carried out. In the present paper, a spatio-temporal analysis of EEG synchronization in 24 patients affected by absence seizure is proposed and the results are hereby reported and compared to the results obtained with a group of 40 healthy subjects. The spatio-temporal analysis is based on Permutation Entropy (PE). We found out that, ever since the interictal stages, fronto-temporal areas appear constantly associated to PE levels that are higher compared to the rest of the brain, whereas the parietal/occipital areas appear associated to low-PE. The brain of healthy subjects seems to behave in a different way because we could not see a recurrent behaviour of PE topography.
机译:时至今日,癫痫发作的起源仍是未知之数。大多数科学家所共有的假设是,不同组神经元的异常同步似乎触发了募集机制,该机制导致大脑癫痫发作以重置这种异常状态。如果是这种情况,可以假设脑电图的特征会逐渐发生变化。因此,有必要找到一个能够测量EEG中同步水平的参数,并且如果我们要找出大脑中不同区域如何相互吸引以发展大脑的能力,则必须考虑空间维度。癫痫发作时,必须对该参数进行时空分析。在本文中,提出了24例因失神发作而受影响的患者的EEG同步的时空分析,并据此报告了该结果,并将其与一组40名健康受试者的结果进行了比较。时空分析基于置换熵(PE)。我们发现,自间隔期以来,额颞区一直与PE水平相关,而PE水平高于大脑其他部位,而顶/枕区则与低PE相关。健康受试者的大脑似乎表现出不同的行为,因为我们看不到PE地形的复发行为。

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