Advanced time-frequency methods for signal-averaged ECG analysis

Frequency-domain techniques have been extensively investigated for the analysis of high-resolution electrocardiograms (ECGs), although the merit of frequency-domain analysis is still subject to controversy. Time-frequency analysis methods, which estimate the frequency content of a signal as a function of time, potentially provide even more information for improved ECG analysis. Some researchers report impressive results in predicting the outcome of electrophysiologic studies using the short-time Fourier transform (spectrogram). Other time-frequency representations, such as the Wigner distribution, short-time spectral estimators, and the wavelet transform, have also been investigated. The authors present a unified overview of time-frequency representations, showing that only four classes characterize most time-frequency representations. The authors describe the advantages and drawbacks of the various approaches and speculate on their promise for ECG analysis. Very preliminary experiments in applying some of these techniques to the prediction of the outcome of electrophysiologic studies have suggested some possible new research directions.