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基于最大似然算法的心电逆问题研究

EM Algorithm for the Inverse Problem of Electrocardiography
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摘要 心电逆问题是通过测得的体表电势分布求取心外膜电势分布的过程,具有重要的临床意义和生理意义。本文采用有限元方法对心脏和体腔进行二维建模并求解心电正问题,然后构建状态空间方程,建模得到的体表电势与心外膜电势之间的关系为系统的测量方程,相邻时刻状态之间的关系为系统的状态方程。对于参数的不确定性问题,建立似然函数,引入期望最大化(Expectation Maximization,EM)算法来求解,步骤E(Expectation)采用卡尔曼滤波对参数进行估计,步骤M(Maximization)利用似然函数重新估计约束,步骤E,步骤M循环迭代。最后对整个过程进行仿真,结果显示采用期望最大化(EM)算法时,解的收敛性要好于传统的卡尔曼滤波的解,相对误差也可以得到大幅度的降低。 The endeavors to solve the inverse problem of electrocardiography embody the approach to calculate the epicardial potentials using the measured body-surface-potential distribution; it is important for pathology and very useful for clinical application. In this paper , we construct the 2D human torso model using the FEM method and solve the forward problem. In the constructed state-space equations, and the relationship between the body surface potentials and epicardial potentials in the FEM torso model is th...
作者 高飞 刘华锋
出处 《生物医学工程学杂志》 EI CAS CSCD 北大核心 2008年第4期795-800,共6页 Journal of Biomedical Engineering
关键词 心电逆问题 有限元模型 EM算法 Inverse problem of electrocardiography Finite element method(FEM) model Expectation Maximization(EM) algorithm
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参考文献10

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