Feature extraction of the atrial fibrillation signal using the continuous wavelet transform

Abstract

Despite advances in cardiac arrhythmia management, atrial fibrillation remains a major cause of cardiovascular morbidity and mortality. Recent data suggests that there are periods of organization within this apparently chaotic arrhythmia. To date, analysis of the rapidly changing atrial fibrillation signal has been limited by a lack of time-frequency resolution. When used to analyze high-density atrial mappings of this arrhythmia, the continuous wavelet transform, with its time-frequency multi-resolution capability, may provide important temporal and spatial information regarding arrhythmia organization and may lead to the development of more effective therapies.