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从房颤病人的体表12导联心电图中得到房颤波信号,是分析和描述房颤特征的重要环节.文中发展了一种基于高阶统计量的盲源提取算法用来获取房颤波信号,模拟数据和临床数据证明了这种算法的可行性和有效性.与盲源分离相关方法相比,盲源提取算法只提取一个所需信号,通过计算频谱集中度的大小,就可以判断它是否为房颤信号,而不必像盲源分离方法那样必须对分离后的12组信号进行复杂的判断才能决定房颤信号.因此,这种方法更适合于应用到临床监护中.
Atrial fibrillation signal obtained from the 12-lead electrocardiogram of body surface of atrial fibrillation is an important link in the analysis and characterization of atrial fibrillation.A new blind source extraction algorithm based on high-order statistics is developed to acquire atrial fibrillation Signal, simulation data and clinical data prove the feasibility and effectiveness of this algorithm.Compared with the blind source separation method, the blind source extraction algorithm only extracts a desired signal, and by calculating the spectrum concentration, we can judge Whether it is an atrial fibrillation signal, and it is not necessary to make complex judgments on the separated 12 groups of signals to decide the atrial fibrillation signal, like the blind source separation method.Thus, this method is more suitable for clinical monitoring.