Abstract
Here we present a method of QT interval measurement for Physionetpsilas online QT Challenge ECG database using the wavelets Daubechies 6 and 8 and Symlet 6 and time plane features. Doing so we found that out of these three wavelets Daubechies 6 gives the best output and when averaged with the interval of time plane feature extraction method it gives least percentage of error with respect to the median reference QT interval as specified by Physionet. Our modified time plane feature extraction scheme along with the wavelet method together produces best results for automated QT wave measurement as its regular verification is important for analyzing cardiac health. This is because delay in cardiac repolarization causes ventricular tachyarrhythmias as well as Torsade de pointes (TdP). A feature of TdP is pronounced prolongation of the QT interval in the supraventricular beat preceding the arrhythmia. TdP can degenerate into ventricular fibrillation, leading to sudden death.
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