Detection and characterization of intermittent complexity variations in cardiac arrhythmia

OBJECTIVE A frequent observation during cardiac fibrillation is a fluctuation in complexity where the irregular pattern of the fibrillation is interrupted by more regular phases of varying length. APPROACH We apply different measures to sliding windows of raw ECG signals for quantifying the temporal complexity. The methods include permutation entropy, power spectral entropy, a measure for the extent of the set of reconstructed states and several wavelet measures. MAIN RESULTS Using these methods, variations of fibrillation patterns over time are detected and visualized. SIGNIFICANCE These quantifications can be used to characterize different phases of the ECG during fibrillation and might improve diagnosis and treatment methods for heart diseases.

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