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.
In this paper a new algorithm is proposed for QRS onset and offset detection in single lead electrocardiogram (ECG) records. In each cardiac cycle, the R peak is first detected to serve as a reference to delimit the search windows for the QRS onset and offset. Then, an auxiliary signal is defined from the envelope of the ECG signal. Finally, a statistical hypothesis test is applied to the auxiliary signal in order to detect mean changes. The performances of the algorithm have been evaluated using the PhysioNet QT database. The mean and standard deviation of the differences between onsets or offsets manually marked by cardiologists and those detected by the proposed algorithm are computed. The standard deviations obtained in this work are around the tolerances accepted by expert physicians, and slightly outperform the results obtained by the other known algorithms evaluated with the same database.
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