本文提出一种由头皮测量脑电逆推皮层电位分布的新方法，使脑电图的空间分辨率明显提高。方法建立在把无源似稳电场过程转化成有限电阻网络过程的基础上。不但可以逐层递推头皮下各层组织结构上的电位分布，而且减少了计算量。仿真计算初步证明了方法的可行性。

    分类号： R318.19

A NEW ALGORITHMFOR FINDING HIGH-RESULUTION EEG

    BASED ON FINITE RESISTANCE NETWORK MODEL

    Pt.Ⅰ CONCENTRIC SPHERE HEAD MODEL

Zhan Wang, Yang Fusheng

    (Dept. of Electrical Engineering, Tsinghua University, 100084)

ABSTRACT

A new method for the deconvolution ofcortical EEG potential distribution from the measured scalp EEG is proposed in this paper,which improves the spatial resolution of EEG considerably. The method is based on theapproximation of passive electric field problem into a Finite Resistance Network problem.Not only the potential distribution on different layers of the head (scalp, skull andcortex) can be computed recursively, but the computation load is also reduced. Thevalidity of the method is shown by computer simulation.

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