Predicting effectiveness of cardiac resynchronization therapy based on QRS decomposition using the Meyer orthogonal wavelet transformation

Cardiac resynchronization therapy (CRT) has shown clinical benefit for patients with heart failure (HF). However, up to one third of these patients do not respond to CRT. The aim of this study is to determine if specific conduction abnormalities are common to patients who respond to CRT and if these can be identified and quantified on the surface ECG. A signal averaging algorithm was developed to enhance the QRS features and decrease the noise level. Then, a Meyer orthogonal wavelet transformation was applied to the ECG to decompose the QRS. The receiver operating characteristic curve (ROC) showed that a combination of wavelet coefficients with clinical factors allowed 80% of sensitivity and specificity using the signal from either lead X or Z. Our preliminary results indicate that time-scale decomposition of the high-resolution QRS signal contains information on predicting individuals´ response to CRT.