In this work two relevant considerations in the ICA-based estimation of atrial activity (AA) in atrial fibrillation (AF) episodes from real electrocardiogram (ECG) recordings are presented. Firstly, the impact of low-pass filtering preprocessing on the extraction quality of AA is analyzed, showing an average improvement over 17% in spectral concentration (SC) when low-pass filtering is applied after ICA with respect to the application of the same filtering before ICA. Secondly, it is demonstrated that the ICA mixing matrix obtained from one AF segment can also be used to estimate the AA present in different segments of the same recording, thus proving the pseudostationarity of the mixing matrix. Results over 32 AF segments show a mean cross-correlation of R̄dp = 81.5% between the directly estimated AA and the estimated using presudostationarity. Changes in spectral concentration from one case to the other (ΔSC̄dp = 1.4%) are negligible. © Springer-Verlag 2004.
CITATION STYLE
Rieta, J. J., Sánchez, C., Sanchis, J. M., Castells, F., & Millet, J. (2004). Mixing matrix pseudostationarity and ECG preprocessing impact on ICA-based atrial fibrillation analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3195, 1079–1086. https://doi.org/10.1007/978-3-540-30110-3_136
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