Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
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The mechanisms responsible for the initiation, maintenance and spontaneous termination of atrial fibrillation (AF) are not yet completely understood. Though much of the underlying physiology has been well determined, it has been demonstrated in numerous clinical investigations that the autonomic nervous system plays an important role in AF genesis and maintenance. In this work the effects of a widely used anaesthetic (propofol) in AF therapies has been studied. ECG recording and 12 intracardiac bipolar leads were recorded from 17 patients diagnosed with AF at both baseline and during anaesthetic infusion, in order to study its effects on AF behavior. By considering all intracardiac leads, the dominant atrial cycle length found at baseline was higher than during propofol infusion, but this difference was not statistically significant. However, the process of averaging results over all 12 leads may obscure clinically significant changes. In order to try to emphasize any differences which may exist, Principal Component Analysis (PCA) and Independent Component Analysis (ICA) were applied. This statistical analysis did show a significant difference between both groups. The shorter cycle lengths found in this study at baseline are consistent with parasympathetic and/or other physiological modulation during anaesthetic infusion and suggest that propofol may have antiarrhythmic properties.