Abstract
In this paper, the effect of reducing noise from ECG signals is investigated by applying filters in compliance with the standards for ECG devices, removing and interpolating low amplitude signals. Torso-tank experiment data was used with electrical activity recorded simultaneously from 128 tank electrodes and 108 epicardial sock electrodes. Subsequently, 10 representative beats were selected for analysis. Tikhonov zero-order regularization method was used to solve the inverse problem for the following groups; raw fullset, filtered fullset, raw low amplitude removed, filtered low amplitude removed, raw low amplitude interpolated, filtered low amplitude interpolated torso signals. Pearson’s correlation was used for comparison between measured and computed electrograms and between activation maps derived from them. Filtering the signal according to the standards improved the reconstructed electrograms. In addition, removal of low amplitude signals and replacing them with interpolated signals combined with filtering according to the standard significantly improved the reconstructed electrograms and derived activation maps.
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Acknowledgments
This project is supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB). This work is also supported by the French National Research Agency (ANR-10-IAHU04-LIRYC).
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Rababah, A., Finlay, D., Bear, L., Bond, R., Rjoob, K., Mclaughlin, J. (2019). Interpolating Low Amplitude ECG Signals Combined with Filtering According to International Standards Improves Inverse Reconstruction of Cardiac Electrical Activity. In: Coudière, Y., Ozenne, V., Vigmond, E., Zemzemi, N. (eds) Functional Imaging and Modeling of the Heart. FIMH 2019. Lecture Notes in Computer Science(), vol 11504. Springer, Cham. https://doi.org/10.1007/978-3-030-21949-9_13
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