心房活动电生理信号特征提取

为从12导联体表心电图中有效地提取反映心房活动的电生理信号,构造一种稀疏表示下的独立成分分析模型。首先,对采集到的12导联体表心电信号进行预处理,然后通过小波变换,实现心电信号小波域的稀疏表示形式,对变换后的心电信号进行独立成分分析,并通过频谱分析确定出反映心房活动的电生理信号源。讨论了平均房颤周长的这一测量指标在房颤患者中的具体应用。实验表明,该方法可以有效提取心房活动的电生理信号,将对心房活动电生理的深入研究产生积极影响。

Features Extraction of Atrial Activity from Surface ECG

In this paper, a novel model of independent component analysis (ICA), based on sparse representation, was proposed to extract atrial activity electrophysiology from 12-leads ECG. Some preprocessing was done upon the acquired 12-leads ECG and the wavelet transform was used to implement the sparse representation of ECG. ICA in wavelet domain was proposed to deal with the transformed coefficients of the 12-leads ECG. The atrial activity electrophysiology, which was separated as an independent source from the transformed coefficients of the 12-leads ECG, was verified by means of spectral analysis. The application of average atrial fibrillation cycle length was discussed in details. Results showed that this new approach had the ability to extract atrial activity electrophysiological signal, having great importance to the mechanisms research of atrial activity electrophysiology.