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A robust wavelet-based multi-lead Electrocardiogram delineation algorithm.

机译:鲁棒的基于小波的多导联心电图描绘算法。

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A robust multi-lead ECG wave detection-delineation algorithm is developed in this study on the basis of discrete wavelet transform (DWT). By applying a new simple approach to a selected scale obtained from DWT, this method is capable of detecting QRS complex, P-wave and T-wave as well as determining parameters such as start time, end time, and wave sign (upward or downward). First, a window with a specific length is slid sample to sample on the selected scale and the curve length in each window is multiplied by the area under the absolute value of the curve. In the next step, a variable thresholding criterion is designed for the resulted signal. The presented algorithm is applied to various databases including MIT-BIH arrhythmia database, European ST-T Database, QT Database, CinC Challenge 2008 Database as well as high resolution Holter data of DAY Hospital. As a result, the average values of sensitivity and positive predictivity Se=99.84% and P+=99.80% were obtained for the detection of QRS complexes, with the average maximum delineation error of 13.7ms, 11.3ms and 14.0ms for P-wave, QRS complex and T-wave, respectively. The presented algorithm has considerable capability in cases of low signal-to-noise ratio, high baseline wander, and abnormal morphologies. Especially, the high capability of the algorithm in the detection of the critical points of the ECG signal, i.e. the beginning and end of T-wave and the end of the QRS complex was validated by cardiologists in DAY hospital and the maximum values of 16.4ms and 15.9ms were achieved as absolute offset error of localization, respectively.
机译:在离散小波变换(DWT)的基础上,提出了一种鲁棒的多导联心电图波检测-描绘算法。通过对从DWT获得的选定比例尺应用新的简单方法,该方法能够检测QRS波,P波和T波以及确定诸如开始时间,结束时间和波浪符号(向上或向下)的参数)。首先,将具有特定长度的窗口滑动到选定比例的样本上,然后将每个窗口中的曲线长度乘以曲线绝对值下的面积。在下一步中,为所得信号设计可变阈值标准。该算法适用于各种数据库,包括MIT-BIH心律失常数据库,欧洲ST-T数据库,QT数据库,CinC Challenge 2008数据库以及DAY医院的高分辨率Holter数据。结果,对于QRS络合物的检测,获得了灵敏度和正预测性的平均值Se = 99.84%和P + = 99.80%,P波的平均最大描绘误差为13.7ms,11.3ms和14.0ms, QRS波和T波分别。该算法在低信噪比,高基线漂移和异常形态的情况下具有相当大的能力。尤其是,该算法在检测ECG信号的关键点(即T波的开始和结束以及QRS复合波的结束)方面具有很高的能力,已被DAY医院的心脏病专家验证,其最大值为16.4ms定位的绝对偏移误差分别达到15.9ms和15.9ms。

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