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Detection of ECG characteristic points using Biorthogonal Spline Wavelet

机译:双正交样条小波检测心电图特征点

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An algorithm based on Biorthogonal Spline Wavelet is developed for detecting ECG characters points. In the algorithm, the Biorthogonal Spline Wavelet Transform of the ECG signal is first calculated using Mallat Algorithm. And then the R-peak is located by finding the best modulus maximum pair of the wavelet transform in the scale of 23. A more robust method to find the modulus maximum pair is put forward in this paper. The methods finding the onsets and offsets of QRS complexes, P and T waves are also provided. The detection rate of QRS complexes for the algorithm is above 99.7% for MIT/BIH database and the processing time is considerably little.
机译:提出了一种基于双正交样条小波的心电图特征点检测算法。在该算法中,首先使用Mallat算法计算ECG信号的双正交样条小波变换。然后通过以2 3 的比例找到小波变换的最佳模最大对来定位R-peak。提出了一种更鲁棒的求模对的方法。还提供了寻找QRS波,P波和T波的起伏和偏移的方法。对于MIT / BIH数据库,该算法QRS络合物的检出率在99.7%以上,处理时间非常短。

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