Key result
A hybrid method combining the Daubechies 6 wavelet and time plane feature extraction produced the least percentage of error for automated QT interval measurement compared to reference values.
Why the study?
Does a hybrid wavelet and time plane based method improve the accuracy of QT interval measurement in ECG signals?
Does a hybrid wavelet and time plane based method improve the accuracy of QT interval measurement in ECG signals?
A hybrid method combining Daubechies 6 wavelet and time plane features provides highly accurate automated QT interval measurements compared to reference standards.
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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Majumder et al. (2008) studied QT interval measurement. Hybrid wavelet (Daubechies 6) and time plane based method vs. Other wavelets (Daubechies 8, Symlet 6) and median reference QT interval was evaluated on Percentage of error with respect to the median reference QT interval. A hybrid method combining the Daubechies 6 wavelet and time plane feature extraction produced the least percentage of error for automated QT interval measurement compared to reference values.
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