Hossain Billal, Bashar Syed Khairul, Walkey Allan J, McManus David D, Chon Ki H
Department of Biomedical Engineering, University of Connecticut, Storrs CT 06269, USA.
Department of Medicine, Boston University School of Medicine, Boston MA 02118, USA.
IEEE Access. 2019;7:128869-128880. doi: 10.1109/access.2019.2939943. Epub 2019 Sep 6.
We developed a novel method for QRS complex and P wave detection in the electrocardiogram (ECG) signal. The approach reconstructs two different signals for the purpose of QRS and P wave detection from the modes obtained by the complete ensemble empirical mode decomposition with adaptive noise, taking only those modes that best represent the signal dynamics. This approach eliminates the need for conventional filtering. We first detect QRS complex locations, followed by removal of QRS complexes from the reconstructed signal to enable P wave detection. We introduce a novel method of P wave detection from both the positive and negative amplitudes of the ECG signal and an adaptive P wave search approach to find the true P wave. Our detection method automatically identifies P waves without prior information. The proposed method was validated on two well-known annotated databases-the MIT BIH Arrythmia database (MITDB) and The QT database (QTDB). The QRS detection algorithm resulted in 99.96% sensitivity, 99.9% positive predictive value, and an error of 0.13% on all validation databases. The P wave detection method had better performance when compared to other well-known methods. The performance of our P wave detection on the QTDB showed a sensitivity of 99.96%, a positive predictive value of 99.47%, and the mean error in P peak detection was less than or equal to one sample (4 ms) on average.
我们开发了一种用于在心电图（ECG）信号中检测QRS复合波和P波的新方法。该方法通过自适应噪声的完全集合经验模式分解获得的模式，为QRS和P波检测重建两个不同的信号，只选取那些最能代表信号动态的模式。这种方法无需传统滤波。我们首先检测QRS复合波的位置，然后从重建信号中去除QRS复合波以进行P波检测。我们引入了一种从ECG信号的正负幅度检测P波的新方法以及一种自适应P波搜索方法来找到真正的P波。我们的检测方法无需先验信息即可自动识别P波。所提出的方法在两个著名的带注释数据库——麻省理工学院贝丝以色列女执事医疗中心心律失常数据库（MITDB）和QT数据库（QTDB）上得到了验证。QRS检测算法在所有验证数据库上的灵敏度为99.96%，阳性预测值为99.9%，误差为0.13%。与其他著名方法相比，P波检测方法具有更好的性能。我们在QTDB上的P波检测性能显示，灵敏度为99.96%，阳性预测值为99.47%，P波峰值检测的平均误差平均小于或等于一个样本（4毫秒）。
