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.