A modified combined wavelet transform technique successfully extracted ECG parameters for cardiac disease diagnostics, with consistency and reliability confirmed by alternate diagnostic criteria.
Does a modified combined wavelet transform technique accurately extract features from ECG signals for the diagnosis of cardiac diseases?
A modified combined wavelet transform technique successfully extracts fundamental ECG parameters for reliable diagnosis of conditions like tachycardia, bradycardia, and ventricular hypertrophy.
This paper deals with a modified combined wavelet transform technique that has been developed to analyse multilead electrocardiogram signals for cardiac disease diagnostics. Two wavelets have been used, i.e. a quadratic spline wavelet (QSWT) for QRS detection and the Daubechies six coefficient (DU6) wavelet for P and T detection. After detecting the fundamental electrocardiogram waves, the desired electrocardiogram parameters for disease diagnostics are extracted. The software has been validated by extensive testing using the CSE DS-3 database and the MIT/BIH database. A procedure has been evolved using electrocardiogram parameters with a point scoring system for diagnosis of cardiac diseases, namely tachycardia, bradycardia left ventricular hypertrophy, and right ventricular hypertrophy. As the diagnostic results are not yet disclosed by the CSE group, two alternate diagnostic criteria have been used to check the diagnostic authenticity of the test results. The consistency and reliability of the identified and measured parameters were confirmed when both the diagnostic criteria gave the same results
Saxena et al. (Tue,) conducted a other in Cardiac diseases (tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy). Modified combined wavelet transform technique (QSWT and DU6 wavelets) vs. Alternate diagnostic criteria was evaluated on Diagnostic authenticity and consistency of identified and measured parameters. A modified combined wavelet transform technique successfully extracted ECG parameters for cardiac disease diagnostics, with consistency and reliability confirmed by alternate diagnostic criteria.