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A new algorithm has been developed for delineation of significant points ofvarious electrocardiographic signal (ECG) waves, taking into accountinformation from all available leads and providing similar or higher accuracyin comparison with other modern technologies. The test results for the QTdatabase show a sensitivity above 97% when detecting ECG wave peaks and 96% fortheir onsets and offsets, as well as better positive predictive value comparedto the previously known algorithms. In contrast to the previously publishedalgorithms, the proposed approach also allows one to determine the morphologyof waves. The segmentation mean errors of all significant points are below thetolerances defined by the Committee of General Standards forElectrocardiography (CSE).

Finding morphology points of electrocardiographic signal waves using wavelet analysis