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A wavelet-based ECG delineator: evaluation on standard databases

机译:基于小波的ECG描绘器:对标准数据库的评估

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In this paper, we developed and evaluated a robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT). In a first step, QRS complexes are detected. Then, each QRS is delineated by detecting and identifying the peaks of the individual waves, as well as the complex onset and end. Finally, the determination of P and T wave peaks, onsets and ends is performed. We evaluated the algorithm on several manually annotated databases, such as MIT-BIH Arrhythmia, QT, European ST-T and CSE databases, developed for validation purposes. The QRS detector obtained a sensitivity of Se=99.66% and a positive predictivity of P+=99.56% over the first lead of the validation databases (more than 980,000 beats), while for the well-known MIT-BIH Arrhythmia Database, Se and P+ over 99.8% were attained. As for the delineation of the ECG waves, the mean and standard deviation of the differences between the automatic and manual annotations were computed. The mean error obtained with the WT approach was found not to exceed one sampling interval, while the standard deviations were around the accepted tolerances between expert physicians, outperforming the results of other well known algorithms, especially in determining the end of T wave.
机译:在本文中,我们基于小波变换(WT)开发并评估了鲁棒的单导联心电图(ECG)描绘系统。第一步,检测QRS复合体。然后,通过检测和识别各个波的峰值以及复杂的开始和结束来描绘每个QRS。最后,确定P和T波的峰值,起点和终点。我们在几个为验证目的而开发的手动注释数据库(例如MIT-BIH心律失常,QT,欧洲ST-T和CSE数据库)上评估了该算法。 QRS检测器相对于验证数据库的第一个导联(超过980,000次)获得了Se = 99.66%的灵敏度和P + = 99.56%的正预测性,而对于著名的MIT-BIH心律失常数据库而言,Se和P +超过99.8%。至于心电图波的描绘,计算了自动和手动注释之间的差异的平均值和标准偏差。发现用WT方法获得的平均误差不超过一个采样间隔,而标准偏差在专家医师之间的可接受公差范围内,优于其他众所周知的算法,尤其是在确定T波结束时。

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