A robust wavelet-based multi-lead electrocardiogram delineation algorithm

Abstract 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 13.7 ms, 11.3 ms and 14.0 ms 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 16.4 ms and 15.9 ms were achieved as absolute offset error of localization, respectively.