Evaluation of a wavelet-based ECG waveform detector on the QT database

In this work we have evaluated a single-lead wavelet transform (WT) based detector of ECG significant points. A quadratic spline wavelet was used as prototype wavelet and the first four scales of the Dyadic WT were analyzed. First of all, we detect QRS complexes. Then, the individual waves, the onset and the offset of the QRS complexes are identified and finally P and T peaks and their onset and offset are detected. We have validated the algorithm with the manual annotations in the Qr Database (QTDB), developed for validation purposes. QRS and other ECG waveform boundaries were independently evaluated. The mean and standard deviation of the differences between the manual and detector's wave boundary annotations were calculated The standard deviations obtained with the WT approach are around the accepted tolerances between expert physicians, outperforming the results of a low-pass differentiator algorithm, which was used as a reference, especially in the T wave offset. The QRS detector obtained a sensitivity of Se=99.91 and a positive predictivity of P+ = 99.8%.