A new algorithm for T-wave end location based on the area covered by the T-wave curve outperformed other algorithms when evaluated on the PhysioNet QT database.
The purpose of this paper is to propose a new algorithm for T-wave end location in electrocardiograms, mainly through the computation of an indicator related to the area covered by the T-wave curve. Based on simple assumptions, essentially on the concavity of the T-wave form, it is formally proved that the maximum of the computed indicator inside each cardiac cycle coincides with the T-wave end. Moreover, the algorithm is robust to acquisition noise, to wave form morphological variations and to baseline wander. It is also computationally very simple: the main computation can be implemented as a simple finite impulse response filter. When evaluated with the PhysioNet QT database in terms of the mean and the standard deviation of the T-wave end location errors, the proposed algorithm outperforms the other algorithms evaluated with the same database, according to the most recent available publications up to our knowledge.
Zhang et al. (Fri,) conducted a other in Electrocardiogram analysis. Proposed algorithm for T-wave end location vs. Other algorithms was evaluated on Mean and standard deviation of T-wave end location errors. A new algorithm for T-wave end location based on the area covered by the T-wave curve outperformed other algorithms when evaluated on the PhysioNet QT database.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: