心房颤动是一种最常见的室上性心律失常。最近的研究表明，大多数持续性房颤患者的心房内同时有多个颤动源共同起作用，体表心电信号中的f波是心房内各颤动源对应的f波子波的线性叠加。本课题重点研究f波分析过程中的两个关键环节，即f波提取和f波分解问题。针对现有的单导联f波提取算法所提取的f波存在局部严重失真的问题，拟分别从信号重构和统计估计的角度展开研究，尽可能达到无失真提取f波的目标，以满足f波新特征量计算和f波分解的需求；为了由多导联体表f波分解获得各颤动源对应的f波子波，拟采用盲源信号分离的相关方法实现f波子波的分离；同时，拟从心电正向问题仿真模型出发，建立心房外膜电势与体表电势的映射模型，在此基础上，探索利用f波子波分离向量实现颤动源位置的无创伤定位；另外，本课题还将积极探索实践f波子波的应用，拟展开f波子波在房颤电复律治疗效果预评估中的应用研究。

Atrial Fibrillation (AF) is the most common super-ventricular arrhythmia. Recent studies show that persistent AF is sustained by multiple localized rotors. That means fabrillatory (f) wave in surface electrocardiogram (ECG) can be decomposed into several daughter-f waves which reflect electrical activity of localized rotors. In this study, we will focus on two key points of f wave analysis, f wave extraction and f wave decomposition. Computation of f wave's new features and f wave decomposition require f wave with less distortion. However, f waves extracted by existing single-lead extraction algorithms are with serious local distortion. In order to obtain f wave without distortion, we will carry out research on single-lead f wave extraction following two ways, namely, signal reconstruction and statistical estimation. To obtain daughter-f wave through decomposition of multi-lead f waves, blind source separation theory would be taken as a key tool. Based on simulation model of ECG forward problem, we will found the model of the relationship between epicardial potential and body surface potential. Based on this model, we will non-invasively estimate the location of localized rotors in atria using daughter-f wave's separation vector. In addition, we will carry on research on daughter-f wave's clinical applications, mainly on predicting outcome of electrical cardioversion for AF patients.