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A novel feature extracting method of QRS complex classification for mobile ECG signals

机译:移动心电信号QRS复杂分类的特征提取新方法

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The conventional classification parameters of QRS complex suffer from larger activity rang of patients and lower signal to noise ratio in mobile cardiac telemonitoring system and can not meet the identification needs of ECG signal. Based on individual sinus heart rhythm template built with mobile ECG signals in time window, we present semblance index to extract the classification features of QRS complex precisely and expeditiously. Relative approximation r2 and absolute error r3 are used as estimating parameters of semblance between testing QRS complex and template. The evaluate parameters corresponding to QRS width and types are demonstrated to choose the proper index. The results show that 99.99 percent of the QRS complex for sinus and superventricular ECG signals can be distinguished through r2 but its average accurate ratio is only 46.16%. More than 97.84 percent of QRS complexes are identified using r3 but its accurate ratio to the sinus and superventricular is not better than r2. By the feature parameter of width, only 42.65 percent of QRS complexes are classified correctly, but its accurate ratio to the ventricular is superior to r2. To combine the respective superiority of three parameters, a nonlinear weighing computation of QRS width, r2 and r3 is introduced and the total classification accuracy up to 99.48% by combing indexes.
机译:QRS复合物的常规分类参数存在患者活动范围较大,移动式心脏远程监护系统信噪比较低,不能满足心电信号识别的需要。基于在时间窗口中使用移动心电信号构建的单个窦性心律模板,我们提出了相似度指标,以快速准确地提取QRS复杂度的分类特征。相对近似值r2和绝对误差r3用作估计QRS复数和模板之间相似度的参数。演示了与QRS宽度和类型相对应的评估参数,以选择适当的索引。结果表明,通过r2可以分辨出99.99%的窦和心室上电心电图QRS波群,但其平均准确率仅为46.16%。使用r3可以识别出超过97.84%的QRS络合物,但其与窦和心室的准确比例并不优于r2。根据宽度的特征参数,只有42.65%的QRS络合物正确分类,但其与心室的准确比率优于r2。为了结合三个参数各自的优势,引入了QRS宽度r2和r3的非线性加权计算,通过合并指标,总分类精度高达99.48%。

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