Discrimination of endocardial electrogram disorganization using a signal regularity analysis
Jazyk angličtina Země Spojené státy americké Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
- MeSH
- algoritmy MeSH
- analýza rozptylu MeSH
- automatizace metody MeSH
- elektrokardiografie metody MeSH
- entropie MeSH
- fibrilace síní patofyziologie MeSH
- fraktály MeSH
- lidé MeSH
- srdeční síně patofyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Measures from the theory of nonlinear dynamics were applied on complex fractionated atrial electrograms (CFAEs) in order to characterize their physiological dynamic behavior. The results were obtained considering 113 short term atrial electrograms (A-EGMs) which were annotated by three experts into four classes of fractionation according to A-EGMs signal regularity. The following measures were applied on A-EGM signals: General Correlation Dimension, Approximate Entropy, Detrended Fluctuation Analysis, Lempel-Ziv Complexity, and Katz-Sevcik, Variance and Box Counting Fractal Dimension. Assessment of disorganization was evaluated by a Kruskal Wallis statistical test. Except Detrended Fluctuation Analysis and Variance Fractal Dimension, the CFAE disorganization was found statistically significant even for low significant level alpha = 0.001. Moreover, the increasing complexity of A-EGM signals was reflected by higher values of General Correlation Dimension of order 1 and Approximate Entropy.
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