Here we present a method of QT interval meas-urement for Physionet's online QT Challenge ECG database using the combination of wavelet and time plane feature extraction mechanisms. For this we mainly combined two previous works one done using the Daubechies 6 wavelet and one time plane based with modifications in their algorithms and inclusion of two more wavelets (Daubechies 8 and Symlet 6). But found that out of these three wavelets Daube-chies 6 and 8 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 re-sults for automated QT wave measurement as its regular verification is important for analyzing cardiac health. For the V2 chest lead particularly whose QT wave is of tremendous significance we have tested on 530 recordings of Physionet. 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 ar-rhythmia. TdP can degenerate into ventricular fibrillation, leading to sudden death.
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