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Apparatus and method for providing information on epilepsy symptoms based on resting-state EEG

机译:基于静息状态脑电图提供癫痫症状信息的设备和方法

摘要

The present invention relates to an apparatus and method for providing epilepsy diagnosis information for diagnosing the presence of epilepsy, and further, the degree of brain network change, using a patient''s resting EEG, which is used to generate a plurality of resting EEG from previously stored medical data. After obtaining, the brainwave data collection unit for classifying and storing according to the degree of change in the brain network; After measuring the patient''s EEG, the EEG measurement unit for extracting and providing only the EEG corresponding to the resting period; A functional connectivity matrix generator for generating a functional connectivity matrix for each resting EEG stored in the EEG data collection unit when learning a neural network, and for generating a functional connectivity matrix for the patient EEG when analyzing a patient EEG; A graph theory analysis unit for grasping a graph theory analysis value by performing a graph theory analysis on the functional connectivity matrix; When learning a neural network, the graph theory analysis value corresponding to each resting EEG stored in the EEG data collection unit is taken as an input condition, and a plurality of learning data having a degree of brain network change as an output condition is generated, and then the plurality of learning A neural network learning unit that repeatedly trains a neural network through data; And an epilepsy analyzer configured to grasp and report a degree of change in a brain network corresponding to a graph theory analysis value derived from the patient''s brain wave using the neural network when analyzing the patient EEG.
机译:本发明涉及一种用于提供癫痫诊断信息以诊断癫痫的存在以及进一步利用患者的静息EEG来诊断脑网络变化程度的设备和方法,其用于产生多个静息EEG从以前存储的医疗数据中获取后,脑电波数据采集单元根据脑网络的变化程度进行分类和存储;在测量患者的脑电图之后,脑电图测量单元仅提取并提供与休息时间相对应的脑电图;功能连接矩阵生成器,用于在学习神经网络时为存储在EEG数据收集单元中的每个静止EEG生成功能连接矩阵,并在分析患者EEG时为患者EEG生成功能连接矩阵。图论分析单元,通过对功能连通性矩阵进行图论分析,掌握图论分析值;在学习神经网络时,将与存储在EEG数据收集单元中的每个静止EEG相对应的图论分析值作为输入条件,并且生成具有一定程度的脑网络变化的学习数据作为输出条件,然后,多个学习神经网络学习单元通过数据反复训练神经网络;并且癫痫分析器被配置为在分析患者的EEG时使用神经网络来掌握并报告与从患者的脑波导出的图论分析值相对应的脑网络中的变化程度。

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