The smoothed Wigner distribution, used with the short-time Fourier transform, is an effective and computationally efficient tool for characterizing the time-frequency distribution of human ventricular fibrillation.
May support efficient VF signal analysis in research; leaves open clinical validation before adoption.
Ventricular fibrillation (VF) is a catastrophic and potentially lethal breakdown of heart rhythm. Despite its importance, it remains poorly understood; there are no effective techniques for predicting or preventing VF, and it can only be reliably terminated by a large current pulse: defibrillation. There is currently great interest in using linear and nonlinear signal processing techniques to characterise recordings of VF. Five episodes of VF were recorded from patients in a Coronary Care Unit. Time–frequency distributions (TFDs) of the first 10 s of these recordings were estimated with the short-time Fourier transform, Wigner–Ville, smoothed Wigner–Ville and Choi–Williams algorithms. The smoothed Wigner distribution was found to give a TFD reasonably free of cross-terms, without the additional computational cost of the Choi–Williams algorithm. Used in tandem with the predictable short-time Fourier transform, the smoothed Wigner TFD is a valuable tool for characterising the TFD of human VF.
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Clayton et al. (1998) studied this question.
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